BEGIN:VCALENDAR VERSION:2.0 PRODID:-//HasGeek//NONSGML Funnel//EN DESCRIPTION:On data engineering and application of ML in diverse domains X-WR-CALDESC:On data engineering and application of ML in diverse domains NAME:The Fifth Elephant 2017 X-WR-CALNAME:The Fifth Elephant 2017 REFRESH-INTERVAL;VALUE=DURATION:PT12H SUMMARY:The Fifth Elephant 2017 TIMEZONE-ID:Asia/Kolkata X-PUBLISHED-TTL:PT12H X-WR-TIMEZONE:Asia/Kolkata BEGIN:VEVENT SUMMARY:Check-in and breakfast DTSTART:20170727T024500Z DTEND:20170727T040000Z DTSTAMP:20260414T144605Z UID:session/SkQLfHPhhrdA4iSjeZmVp7@hasgeek.com SEQUENCE:0 CREATED:20170515T024847Z DESCRIPTION:\n LAST-MODIFIED:20170809T080122Z LOCATION:Bangalore ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com BEGIN:VALARM ACTION:display DESCRIPTION:Check-in and breakfast in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Stretching session DTSTART:20170727T040000Z DTEND:20170727T041000Z DTSTAMP:20260414T144605Z UID:session/UK87cVchuqD6YR6oWZ9jUK@hasgeek.com SEQUENCE:0 CREATED:20170712T080915Z DESCRIPTION:\n LAST-MODIFIED:20170724T123205Z LOCATION:Auditorium - MLR Convention Centre\, Whitefield\nBengaluru\, \nIN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com BEGIN:VALARM ACTION:display DESCRIPTION:Stretching session in Auditorium in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:HasGeek app demo DTSTART:20170727T040000Z DTEND:20170727T041000Z DTSTAMP:20260414T144605Z UID:session/5jMSjHhESoNZYZEuw99tQf@hasgeek.com SEQUENCE:0 CREATED:20170722T144443Z DESCRIPTION:\n LAST-MODIFIED:20170725T053315Z LOCATION:Banquet hall - MLR Convention Centre\, Whitefield\nBengaluru\, \n IN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com BEGIN:VALARM ACTION:display DESCRIPTION:HasGeek app demo in Banquet hall in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Lessons learned from building a globally distributed database serv ice from the ground up. DTSTART:20170727T041000Z DTEND:20170727T045500Z DTSTAMP:20260414T144605Z UID:session/K1QufNT1FdLq2ksDrorxyc@hasgeek.com SEQUENCE:2 CATEGORIES:Full talk for data engineering track,Intermediate CREATED:20170712T074911Z DESCRIPTION:1. What does it mean to build a database that leverages the st rengths of cloud?\n2. Horizontal partitioning \n3. Elastically scaling thr oughput (vs. storage) worldwide\n4. Resource governance and fine grained m ulti-tenancy\n5. Global distribution of data for low latency\n6. Global di stribution of data for high availability\n7. Navigating the speed of light \n8. Navigating the CAP theorem\n9. Consistency Models - finding the righ t shade of grey!\n10. Why hosting on-premises databases (SQL or NoSQL) can not offer the lowest TCO and best SLAs?\n11. What does it take to offer an d maintain comprehensive SLAs for consistency\, latency and throughput and availability.\n12. Operating a globally distributed database service\, wo rldwide \n13. Insights from the production workloads\n14. Conclusions\n\nA n old deck (I will be using a variation of this presentation):\nhttps://sp eakerdeck.com/dharmashukla/azure-cosmos-db-lessons-learnt-from-building-a- globally-distributed-database-from-the-ground-up\n\n### Speaker bio\n\nDha rma Shukla is a Distinguished Engineer at Microsoft. Dharma is also the fo under of Azure Cosmos DB (http://cosmosdb.com) - a globally distributed\, multi-tenant database service on Azure. Prior to working on the current sy stem\, his work spanned a range of distributed systems and databases at Mi crosoft and other places.\n LAST-MODIFIED:20230810T072606Z LOCATION:Auditorium - MLR Convention Centre\, Whitefield\nBengaluru\, \nIN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com URL:https://hasgeek.com/fifthelephant/2017/schedule/lessons-learned-from-b uilding-a-globally-distributed-database-service-from-the-ground-up-K1QufNT 1FdLq2ksDrorxyc BEGIN:VALARM ACTION:display DESCRIPTION:Lessons learned from building a globally distributed database service from the ground up. in Auditorium in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:How we built our machine intelligence to help humans save lives. DTSTART:20170727T041000Z DTEND:20170727T045500Z DTSTAMP:20260414T144605Z UID:session/7zwcpGWKB4Qrn2VWUZBHA2@hasgeek.com SEQUENCE:2 CATEGORIES:Full talk for Data in Government track ,Beginner CREATED:20170722T144337Z DESCRIPTION:Forthcoming\n\n### Speaker bio\n\nZainul Charbiwala is a co-fo under and the CTO at Tricog Health. He's been building embedded systems\, creating and managing teams and developing software for over 15 years. He is interested in the overlap of connected devices and machine intelligence to revolutionise and reinvent healthcare. He holds a Master's degree from IIT Bombay and a PhD from University of California\, Los Angeles. Before Tricog\, Zainul was a Research Staff Member and Research Manager in the Sm arter Planet Solutions group at IBM Research\, India. Zainul has 7 patents and over 30 refereed publications.\n LAST-MODIFIED:20230810T072606Z LOCATION:Banquet hall - MLR Convention Centre\, Whitefield\nBengaluru\, \n IN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com URL:https://hasgeek.com/fifthelephant/2017/schedule/how-we-built-our-machi ne-intelligence-to-help-humans-save-lives-7zwcpGWKB4Qrn2VWUZBHA2 BEGIN:VALARM ACTION:display DESCRIPTION:How we built our machine intelligence to help humans save live s. in Banquet hall in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Fraud detection and risk management in payment systems implemented using a hybrid memory database. DTSTART:20170727T045500Z DTEND:20170727T054000Z DTSTAMP:20260414T144605Z UID:session/Lasjp3Gmy91WtZcQAxEk6c@hasgeek.com SEQUENCE:2 CATEGORIES:Full talk in Payment Analytics track,Intermediate CREATED:20170712T075210Z DESCRIPTION:https://drive.google.com/file/d/0B80IhwYPI7JWcWM0VVUzNGNHTkU/v iew?usp=sharing\n\n### Speaker bio\n\nDr. Srini V. Srinivasan is Founder a nd Chief Development Officer at Aerospike. \n\nWhen it comes to databases\ , Srini is one of the recognized pioneers of Silicon Valley. He has two de cades of experience designing\, developing and operating high scale infras tructures. He has over 25 patents in database\, web\, mobile and distribut ed systems technologies. His career includes high-profile technical and ex ecutive management roles at IBM\, Liberate and Yahoo!.\n\nSrini co-founded Aerospike to solve the scaling problems he experienced with Oracle databa ses at Yahoo! where\, as Senior Director of Engineering\, he had responsib ility for the development\, deployment and 24×7 operations of Yahoo!’s mobile products. Srini is an M.S./ Ph.D. holder from the University of Wis consin-Madison and is an alumnus of IIT Madras.\n LAST-MODIFIED:20230810T072606Z LOCATION:Auditorium - MLR Convention Centre\, Whitefield\nBengaluru\, \nIN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com URL:https://hasgeek.com/fifthelephant/2017/schedule/fraud-detection-risk-m anagement-in-payment-systems-implemented-using-a-hybrid-memory-database-La sjp3Gmy91WtZcQAxEk6c BEGIN:VALARM ACTION:display DESCRIPTION:Fraud detection and risk management in payment systems impleme nted using a hybrid memory database. in Auditorium in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Stretching session DTSTART:20170727T045500Z DTEND:20170727T050500Z DTSTAMP:20260414T144605Z UID:session/My9DuwZdUryqHPWstySNHH@hasgeek.com SEQUENCE:0 CREATED:20170515T025246Z DESCRIPTION:\n LAST-MODIFIED:20170724T123200Z LOCATION:Banquet hall - MLR Convention Centre\, Whitefield\nBengaluru\, \n IN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com BEGIN:VALARM ACTION:display DESCRIPTION:Stretching session in Banquet hall in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Sponsored talk: Developing and deploying analytics for IoT. DTSTART:20170727T050500Z DTEND:20170727T052500Z DTSTAMP:20260414T144605Z UID:session/9wgk1chUC6XN3dKMKbTdcP@hasgeek.com SEQUENCE:2 CATEGORIES:Sponsored session ,Intermediate CREATED:20170712T092259Z DESCRIPTION:Highlights:\n\nCollecting and storing data on cloud\nIntegrati ng online analysis and visualization using MATLAB\nScaling IoT solutions w ith analytics\n\n### Speaker bio\n\nAmit Doshi is a senior application eng ineer at MathWorks India and is key technical advisor and product advocate for "Data Analytics". Amit has over 10 years of work experience and has p reviously worked at Suzlon Energy Limited in Pune and Germany\, Texas Inst ruments in Germany\, and IIT Bombay. Amit holds a bachelor’s degree in M echanical engineering and a master’s degree in Mechatronics.\n LAST-MODIFIED:20230810T072606Z LOCATION:Banquet hall - MLR Convention Centre\, Whitefield\nBengaluru\, \n IN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com URL:https://hasgeek.com/fifthelephant/2017/schedule/sponsored-talk-develop ing-and-deploying-analytics-for-internet-of-things-iot-9wgk1chUC6XN3dKMKbT dcP BEGIN:VALARM ACTION:display DESCRIPTION:Sponsored talk: Developing and deploying analytics for IoT. in Banquet hall in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Interactive real-time dashboards on data streams using Kafka\, Dru id and Superset. DTSTART:20170727T052500Z DTEND:20170727T060500Z DTSTAMP:20260414T144605Z UID:session/QoiHiJEB41rT7mTM3iZ6oA@hasgeek.com SEQUENCE:2 CATEGORIES:Full talk for data engineering track,Intermediate CREATED:20170712T081848Z DESCRIPTION:Introduction\nArchitecture\nDemo\nApache Kafka as Streaming an d Processing Layer.\nDruid as Serving Layer\nSuperset as Visualization lay er\nKey features of Analytics Stack\nPerformance benchmarks\n\n### Speaker bio\n\nNishant is Druid PMC member and Software Engineer at Hortonworks. He is part of Business Intelligence team at Hortonworks. Prior to that he was part of Metamarkets backend team and was responsible for analytics inf rastructure\, including real-time analytics in Druid. He holds a B.Tech in Computer Science from National Institute of Technology\, Kurukshetra\, In dia.\n LAST-MODIFIED:20230810T072606Z LOCATION:Banquet hall - MLR Convention Centre\, Whitefield\nBengaluru\, \n IN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com URL:https://hasgeek.com/fifthelephant/2017/schedule/interactive-realtime-d ashboards-on-data-streams-using-kafka-druid-and-superset-QoiHiJEB41rT7mTM3 iZ6oA BEGIN:VALARM ACTION:display DESCRIPTION:Interactive real-time dashboards on data streams using Kafka\, Druid and Superset. in Banquet hall in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Morning beverage break (auditorium) DTSTART:20170727T054000Z DTEND:20170727T061500Z DTSTAMP:20260414T144605Z UID:session/Ktj8qriPqDQwfuKbSBdP8y@hasgeek.com SEQUENCE:0 CREATED:20170515T025107Z DESCRIPTION:\n LAST-MODIFIED:20170724T024956Z LOCATION:Auditorium - MLR Convention Centre\, Whitefield\nBengaluru\, \nIN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com BEGIN:VALARM ACTION:display DESCRIPTION:Morning beverage break (auditorium) in Auditorium in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Morning beverage break (banquet hall) DTSTART:20170727T060500Z DTEND:20170727T063500Z DTSTAMP:20260414T144605Z UID:session/9aLH8VSUNftBbokciExYv9@hasgeek.com SEQUENCE:0 CREATED:20170712T093424Z DESCRIPTION:\n LAST-MODIFIED:20170724T024931Z LOCATION:Banquet hall - MLR Convention Centre\, Whitefield\nBengaluru\, \n IN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com BEGIN:VALARM ACTION:display DESCRIPTION:Morning beverage break (banquet hall) in Banquet hall in 5 min utes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Introductions to The Fifth Elephant and Anthill Inside\; HasGeek a pp demo DTSTART:20170727T061500Z DTEND:20170727T063000Z DTSTAMP:20260414T144605Z UID:session/Mp7iqnrBi6Z7VAXiSC9zfp@hasgeek.com SEQUENCE:0 CREATED:20170515T025445Z DESCRIPTION:\n LAST-MODIFIED:20170725T053327Z LOCATION:Auditorium - MLR Convention Centre\, Whitefield\nBengaluru\, \nIN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com BEGIN:VALARM ACTION:display DESCRIPTION:Introductions to The Fifth Elephant and Anthill Inside\; HasGe ek app demo in Auditorium in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Distributed consensus and data safety: NewSQL perspective DTSTART:20170727T063000Z DTEND:20170727T071500Z DTSTAMP:20260414T144605Z UID:session/MBnNvz1q4PXUQRPZGmMfYP@hasgeek.com SEQUENCE:2 CATEGORIES:Full talk for data engineering track,Intermediate CREATED:20170718T124220Z DESCRIPTION:1. Data safety issues in distributed systems\n2. Overview of P axos and Distribtued consensus algorithms\n3. NewSQL datastores - brief on GoogleSpanner\, Clusterix\, NimbusDB etc. \n3. IronFleet and formal verif ication of safety properties of distributed systems.\n\n### Speaker bio\n\ nDr. Vijay Srinivas Agneeswaran has a Bachelor’s degree in Computer Scie nce & Engineering from SVCE\, Madras University (1998)\, an MS (By Researc h) from IIT Madras in 2001\, a PhD from IIT Madras (2008) and a post-docto ral research fellowship in the LSIR Labs\, Swiss Federal Institute of Tech nology\, Lausanne (EPFL). He has joined as Director of Technology in the d ata sciences team of SapientNitro. He has spent the last ten years creatin g intellectual property and building products in the big data area in Orac le\, Cognizant and Impetus. He has built PMML support into Spark/Storm and realized several machine learning algorithms such as LDA\, Random Forests over Spark. He led a team that designed and implemented a big data govern ance product for a role-based fine-grained access control inside of Hadoop YARN. He and his team have also built the first distributed deep learnin g framework on Spark. He is a professional member of the ACM and the IEEE (Senior) for the last 10+ years. He has four full US patents and has publi shed in leading journals and conferences\, including IEEE transactions. Hi s research interests include distributed systems\, data sciences as well a s Big-Data and other emerging technologies. He has been an invited speaker in several national and International conferences such as O'Reilly's Stra ta Big-data conference series. He will also be speaking at the Strata Big- data conference in London in May 2017. He also gave a keynote speech at th e Fifth Elephant conference in 2014. He lives in Bangalore with his wife\, son and daughter and enjoys researching history and philosophy of Egypt\, Babylonia\, Greece and India.\n LAST-MODIFIED:20230810T072606Z LOCATION:Auditorium - MLR Convention Centre\, Whitefield\nBengaluru\, \nIN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com URL:https://hasgeek.com/fifthelephant/2017/schedule/distributed-consensus- and-data-safety-newsql-perspective-MBnNvz1q4PXUQRPZGmMfYP BEGIN:VALARM ACTION:display DESCRIPTION:Distributed consensus and data safety: NewSQL perspective in A uditorium in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Transforming India's budgets into open linked data. DTSTART:20170727T063500Z DTEND:20170727T070500Z DTSTAMP:20260414T144605Z UID:session/FynkyMZykaBZ6bWVipgb5Z@hasgeek.com SEQUENCE:2 CATEGORIES:Full talk for Data in Government track ,Intermediate CREATED:20170712T092351Z DESCRIPTION:The session will be organized as:\n\n- Setting the scene\n- Ma jor issues with Indian Budget Documents\n- Role of Open Source + Communiti es\n- Key components of our Open Data Pipeline: Scrape\, Parse\, Transform \, Publish\, Analyse\n- Open Linked Data: Benefits and Usage \n- Various Analysis Tools \n- Quick Demo(if time permits)\n- Future\n- Questions\n\n# ## Speaker bio\n\nBuilding OpenBudgetsIndia.org | Doing data-for-good at D ataKind Bangalore\n LAST-MODIFIED:20230810T072606Z LOCATION:Banquet hall - MLR Convention Centre\, Whitefield\nBengaluru\, \n IN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com URL:https://hasgeek.com/fifthelephant/2017/schedule/transforming-indias-bu dgets-into-open-linked-data-FynkyMZykaBZ6bWVipgb5Z BEGIN:VALARM ACTION:display DESCRIPTION:Transforming India's budgets into open linked data. in Banquet hall in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Open data in government: challenges\, and the case of Telangana Op en Data initiative. DTSTART:20170727T070500Z DTEND:20170727T073500Z DTSTAMP:20260414T144605Z UID:session/FJ4Vgs3qaVt8tB4yTQtbpK@hasgeek.com SEQUENCE:2 CATEGORIES:Full talk for Data in Government track ,Beginner CREATED:20170712T080257Z DESCRIPTION:This talk will cover:\n\n1. The challenges involved in opening up government data.\n2. The issue of culture\, and why it plays an import ant role in opening up government data. \n3. The role of RTI in opening go vernment data\n4. Current status of the Telangana Open Data Initiative and future plans.\n5. How the Community can participate in the Telangana Open Data Initiative.\n\n### Speaker bio\n\nRakesh Dubbudu is the founder of ‘FACTLY’ (www.factly.in)\, an initiative aimed at making government da ta/information meaningful for the common citizen. Within a short period of time\, Factly has come to be as known as one of the best in the public in formation/data space. Under Rakesh’s leadership\, Factly also won the fi rst ever Innovation for Good1 award in 2015 instituted by Centre for Work\ , Technology and Social Change in collaboration with SASNET at Lund Univer sity\, one of Europe’s oldest University. Factly is also featured as a u se case in the Open Data Impact Map2 of the World Bank Group.\n\nRakesh Du bbudu is also a well-known transparency campaigner in India and has been w orking on Right to Information (RTI) related issues for the last decade. H e is currently one of the co-convenors of the National Campaign for People 's Right to Information (NCPRI). He played an instrumental in some of the well-known research studies on RTI.\n\nRakesh brings immense experience in dealing with Government Data\, Policy and various government related info rmation. He is an engineering graduate from NIT Warangal.\n\nRakesh & Fact ly are playing a significant role in ‘Open Data Initiative’ of the Gov ernment of Telangana\,the newest state in India. He has been helping the G overnment of Telangana with many other e-governance/good governance initia tives.\n\nHe has also a visiting faculty at various administrative trainin g institutes of the state & central governments on the subject of RTI.\n LAST-MODIFIED:20230810T072606Z LOCATION:Banquet hall - MLR Convention Centre\, Whitefield\nBengaluru\, \n IN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com URL:https://hasgeek.com/fifthelephant/2017/schedule/open-data-in-governmen t-challenges-and-the-case-of-telangana-open-data-initiative-FJ4Vgs3qaVt8tB 4yTQtbpK BEGIN:VALARM ACTION:display DESCRIPTION:Open data in government: challenges\, and the case of Telangan a Open Data initiative. in Banquet hall in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Stretching session DTSTART:20170727T071500Z DTEND:20170727T072500Z DTSTAMP:20260414T144605Z UID:session/AbpBfVUeNxW6SwkPZ1T7YK@hasgeek.com SEQUENCE:0 CREATED:20170722T161014Z DESCRIPTION:\n LAST-MODIFIED:20170724T123222Z LOCATION:Auditorium - MLR Convention Centre\, Whitefield\nBengaluru\, \nIN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com BEGIN:VALARM ACTION:display DESCRIPTION:Stretching session in Auditorium in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:What database? - a practical guide to selection from NoSQL\, SQL a nd Polyglot data stores DTSTART:20170727T072500Z DTEND:20170727T081000Z DTSTAMP:20260414T144605Z UID:session/Kt53tMgE2okyq2uP5aQFni@hasgeek.com SEQUENCE:2 CATEGORIES:Full talk for data engineering track,Intermediate CREATED:20170712T075235Z DESCRIPTION:- Introduction : talk about how a developer is spoilt for choi ce\, landscape of databases/datastores available.\n- Database types : Rela tional\, Columnar\, KV etc.\n- Storage choices : Append-only\, In-place up dates\n- Different guarantees : Durability\, CAP properties\, Replication\ n- Gotchas and ways to validate DB vendor claims. E.g. Jepsen tests\n- Pol yglot persistence : How to build large database like Aadhaar\, Flipkart ca talog that scales to billion+ data records and can serve millions of reque sts per second\n- Challenges in using polyglot persistence\n- Case studies and examples from Aadhaar\, Flipkart and HealthFace/CureFit at appropriat e points in the discussion\n\n### Speaker bio\n\nRegunath is an open sourc e developer\, engineer who built Aadhaar and later was responsible for Fli pkart platform services. He is currently at HealthFace building data-drive n decision systems for healthcare and personal health records.\n LAST-MODIFIED:20230810T072606Z LOCATION:Auditorium - MLR Convention Centre\, Whitefield\nBengaluru\, \nIN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com URL:https://hasgeek.com/fifthelephant/2017/schedule/what-database-a-practi cal-guide-to-selection-from-nosql-sql-and-polyglot-data-stores-Kt53tMgE2ok yq2uP5aQFni BEGIN:VALARM ACTION:display DESCRIPTION:What database? - a practical guide to selection from NoSQL\, S QL and Polyglot data stores in Auditorium in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Lunch break (banquet hall) DTSTART:20170727T073500Z DTEND:20170727T083500Z DTSTAMP:20260414T144605Z UID:session/BFU5YNZPSL8GUNv2cTEsnZ@hasgeek.com SEQUENCE:0 CREATED:20170712T093820Z DESCRIPTION:\n LAST-MODIFIED:20170724T025021Z LOCATION:Banquet hall - MLR Convention Centre\, Whitefield\nBengaluru\, \n IN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com BEGIN:VALARM ACTION:display DESCRIPTION:Lunch break (banquet hall) in Banquet hall in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Lunch break (auditorium) DTSTART:20170727T081000Z DTEND:20170727T091000Z DTSTAMP:20260414T144605Z UID:session/sUKSi4nkeUAANxskC4QT4@hasgeek.com SEQUENCE:0 CREATED:20170515T051858Z DESCRIPTION:\n LAST-MODIFIED:20170722T161040Z LOCATION:Auditorium - MLR Convention Centre\, Whitefield\nBengaluru\, \nIN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com BEGIN:VALARM ACTION:display DESCRIPTION:Lunch break (auditorium) in Auditorium in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Off The Record (OTR) session: "Using open data in different scenar ios – challenges and opportunities." DTSTART:20170727T083500Z DTEND:20170727T093500Z DTSTAMP:20260414T144605Z UID:session/GytPCaw6smD84b9CiSM3KE@hasgeek.com SEQUENCE:0 CREATED:20170718T124846Z DESCRIPTION:\n LAST-MODIFIED:20170724T124656Z LOCATION:Room 1 - MLR Convention Centre\, Whitefield\nBengaluru\, \nIN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com BEGIN:VALARM ACTION:display DESCRIPTION:Off The Record (OTR) session: "Using open data in different sc enarios – challenges and opportunities." in Room 1 in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Wait\, I can explain this! ML models explaining their predictions. DTSTART:20170727T083500Z DTEND:20170727T085500Z DTSTAMP:20260414T144605Z UID:session/G433M7vXeLhei57gc2xy8e@hasgeek.com SEQUENCE:2 CATEGORIES:Crisp talk for data engineering track,Intermediate CREATED:20170722T145213Z DESCRIPTION:1. Motivation behind the problem statement\n2. Local & Interpr etable explanations\n3. Overall system design\n4. Case study - Our churn p redictor\n5. Questions\n\n### Speaker bio\n\nOwn the Machine Learning / De ep Learning product stack at Zoho Corporation. Have made high impact full stack ML/DL releases\, reaching over a million users and have scaled and t weaked the platform accordingly!\n LAST-MODIFIED:20230810T072606Z LOCATION:Banquet hall - MLR Convention Centre\, Whitefield\nBengaluru\, \n IN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com URL:https://hasgeek.com/fifthelephant/2017/schedule/wait-i-can-explain-thi s-ml-models-explaining-their-predictions-G433M7vXeLhei57gc2xy8e BEGIN:VALARM ACTION:display DESCRIPTION:Wait\, I can explain this! ML models explaining their predicti ons. in Banquet hall in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Stretching session DTSTART:20170727T085500Z DTEND:20170727T090500Z DTSTAMP:20260414T144605Z UID:session/QJR4iX7nXQqWsqeGDUp45v@hasgeek.com SEQUENCE:0 CREATED:20170712T081123Z DESCRIPTION:\n LAST-MODIFIED:20170724T123248Z LOCATION:Banquet hall - MLR Convention Centre\, Whitefield\nBengaluru\, \n IN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com BEGIN:VALARM ACTION:display DESCRIPTION:Stretching session in Banquet hall in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:From a recommendations carousel to personalizing entire app: perso nalization story at Paytm. DTSTART:20170727T090500Z DTEND:20170727T095000Z DTSTAMP:20260414T144605Z UID:session/QP14YNtK7vwWj61fkr1NT@hasgeek.com SEQUENCE:2 CATEGORIES:Full talk in Payment Analytics track,Advanced CREATED:20170722T145753Z DESCRIPTION:At paytm we value user experience and we want to pre-emptively show a user the types of products they would want to buy. In this talk\, we will walk our audience through how we personalize every pixel on our ap p. How do we use deep learning on tens of terabytes of data everyday to so rt long tail merchandise and how we use an ensemble of several models to g enerate every recommendation. We will share our learnings from trying seve ral iterations of models and we will show why standard recommendation tech niques are not widely applicable and why we had to come up with our own fr amework for solving these problems.\n\n### Speaker bio\n\nCharu is a seaso ned machine learning and big data technology leader with over 11 years of experience\nbuilding data products for companies like Amazon\, Canadian Ti re and Accenture.\nAt Paytm\, Charu manages data product teams like person alization\, seller scoring\, customer scoring and\nproduct forecasting.\nC harumitra is a hands on leader with experience leveraging machine learning in many verticals like\npersonalization\, retail merchandise planning\, l oyalty marketing\, digital analytics\, supply chain modeling\nand operatio ns optimization. He has expertise in setting up data science teams and sca ling them to\nautomate decision making using machine learning.\nPrior to P aytm\, Charu\, setup first data science team at Amazon in Canada. Prior to that he was Solutions\nArchitect at Canada’s largest retailer helping t hem setup big data and analytics team responsible for\nmanaging assortment across 1000+ stores.\nCharumitra Pujari has graduated from the McMaster U niversity with a Masters in Engineering.\n LAST-MODIFIED:20230810T072606Z LOCATION:Banquet hall - MLR Convention Centre\, Whitefield\nBengaluru\, \n IN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com URL:https://hasgeek.com/fifthelephant/2017/schedule/from-a-recommendations -carousel-to-personalizing-entire-app-personalization-story-at-paytm-QP14Y NtK7vwWj61fkr1NT BEGIN:VALARM ACTION:display DESCRIPTION:From a recommendations carousel to personalizing entire app: p ersonalization story at Paytm. in Banquet hall in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Q&A with speakers on data stores and databases. DTSTART:20170727T091000Z DTEND:20170727T093000Z DTSTAMP:20260414T144605Z UID:session/6fA7WDsKktZaXKEnitayFk@hasgeek.com SEQUENCE:0 CREATED:20170722T160805Z DESCRIPTION:\n LAST-MODIFIED:20170722T164012Z LOCATION:Auditorium - MLR Convention Centre\, Whitefield\nBengaluru\, \nIN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com BEGIN:VALARM ACTION:display DESCRIPTION:Q&A with speakers on data stores and databases. in Auditorium in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Stretching session DTSTART:20170727T093000Z DTEND:20170727T094000Z DTSTAMP:20260414T144605Z UID:session/5k6ZXNYJumm4b7CmPEbrNy@hasgeek.com SEQUENCE:0 CREATED:20170515T025138Z DESCRIPTION:\n LAST-MODIFIED:20170724T123230Z LOCATION:Auditorium - MLR Convention Centre\, Whitefield\nBengaluru\, \nIN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com BEGIN:VALARM ACTION:display DESCRIPTION:Stretching session in Auditorium in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Distributed ML: challenges and opportunities. DTSTART:20170727T094000Z DTEND:20170727T100000Z DTSTAMP:20260414T144605Z UID:session/KDKyUn19iAs4Q2pbU87QPu@hasgeek.com SEQUENCE:2 CATEGORIES:Crisp talk for data engineering track,Intermediate CREATED:20170722T161144Z DESCRIPTION:* Traditional Machine Learning and opputinities for parallism\ n* Available solutions for distributing and the challenges\n* Our aproach\ n* Learnings from our experiments\n\n### Speaker bio\n\nAnand has been cra fting beautiful software since a decade and half. He’s now building a da ta science platform\, [rorodata](http://rorodata.com/)\, which he recently co-founded. He regularly conducts advanced programming courses through [P ipal Academy](https://pipal.in/). He is co-author of [web.py](http://webpy .org/)\, a micro web framework in Python. He has worked at Strand Life Sci ences and Internet Archive.\n LAST-MODIFIED:20230810T072606Z LOCATION:Auditorium - MLR Convention Centre\, Whitefield\nBengaluru\, \nIN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com URL:https://hasgeek.com/fifthelephant/2017/schedule/distributed-machine-le arning-challenges-and-oppurtunities-KDKyUn19iAs4Q2pbU87QPu BEGIN:VALARM ACTION:display DESCRIPTION:Distributed ML: challenges and opportunities. in Auditorium in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Off The Record (OTR) session: "Interesting problems to solve with data science." DTSTART:20170727T094500Z DTEND:20170727T103000Z DTSTAMP:20260414T144605Z UID:session/KcLccH87URNbQY9ZWZnHqj@hasgeek.com SEQUENCE:0 CREATED:20170712T101220Z DESCRIPTION:\n LAST-MODIFIED:20170724T025205Z LOCATION:Room 1 - MLR Convention Centre\, Whitefield\nBengaluru\, \nIN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com BEGIN:VALARM ACTION:display DESCRIPTION:Off The Record (OTR) session: "Interesting problems to solve w ith data science." in Room 1 in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Adapting bandit algorithms to optimise user experience at Practo C onsult. DTSTART:20170727T095000Z DTEND:20170727T101000Z DTSTAMP:20260414T144605Z UID:session/PPoMUCNyP4YbG3KLic7JTt@hasgeek.com SEQUENCE:2 CATEGORIES:Crisp talk for data engineering track,Intermediate CREATED:20170722T145153Z DESCRIPTION:1. The dynamics of a QnA platform like Practo Consult\n2. Intr oducing Multi-armed Bandit algorithm\n3. Adapting a version of Bandit algo rithm called Contextual Multi-armed Bandit to enhance the experience of us ers and doctors.\n\n### Speaker bio\n\nSantosh GSK is working as a Senior Data Scientist at Practo. He has 5 years of industry experience in Data Sc ience and 3 years as a ML Researcher with half a dozen publications in lea ding conferences. He is currently working on building data-driven solution s to improve both patient and doctor experience at Practo. Prior to that\, he was working as a Data Scientist at Housing.com\, where he worked on le ad prediction and property price prediction models.\n LAST-MODIFIED:20230810T072606Z LOCATION:Banquet hall - MLR Convention Centre\, Whitefield\nBengaluru\, \n IN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com URL:https://hasgeek.com/fifthelephant/2017/schedule/adapting-bandit-algori thms-to-optimise-user-experience-at-practo-consult-PPoMUCNyP4YbG3KLic7JTt BEGIN:VALARM ACTION:display DESCRIPTION:Adapting bandit algorithms to optimise user experience at Prac to Consult. in Banquet hall in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Suuchi: toolkit to build distributed systems. DTSTART:20170727T100000Z DTEND:20170727T103000Z DTSTAMP:20260414T144605Z UID:session/TeZqFzyKerNbTGBSxHtiYn@hasgeek.com SEQUENCE:2 CATEGORIES:Full talk for data engineering track,Intermediate CREATED:20170722T161157Z DESCRIPTION:- Context setting for the topic: bring in notion of distribute d systems and the need for state\n- Complexities involved & advantages if done right\n- Common problems to be solved when building them\n- What does Suuchi provide\n- Suuchi @ Indix\n- Example code\n- Learning & take aways \n\n### Speaker bio\n\n[Sriram R](https://github.com/brewkode) is one of t he early members of the Engineering team at Indix and has been part of var ious systems that is 'live' in production today. Apart from writing code t o foot his bills\, he does it to get some adrenaline going\, when he is no t riding his bike on unchartered terrains. He is co-author of Suuchi proje ct along with his fellow engineer Ashwanth kumar. Currently\, he works on problems involving ML at Indix.\n LAST-MODIFIED:20230810T072606Z LOCATION:Auditorium - MLR Convention Centre\, Whitefield\nBengaluru\, \nIN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com URL:https://hasgeek.com/fifthelephant/2017/schedule/suuchi-toolkit-to-buil d-distributed-systems-TeZqFzyKerNbTGBSxHtiYn BEGIN:VALARM ACTION:display DESCRIPTION:Suuchi: toolkit to build distributed systems. in Auditorium in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Evening beverage break (banquet hall) DTSTART:20170727T101000Z DTEND:20170727T104000Z DTSTAMP:20260414T144605Z UID:session/EyTSynU7EQKm18o8ndU4dY@hasgeek.com SEQUENCE:0 CREATED:20170519T052419Z DESCRIPTION:\n LAST-MODIFIED:20170724T025135Z LOCATION:Banquet hall - MLR Convention Centre\, Whitefield\nBengaluru\, \n IN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com BEGIN:VALARM ACTION:display DESCRIPTION:Evening beverage break (banquet hall) in Banquet hall in 5 min utes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Evening beverage break (auditorium) DTSTART:20170727T103000Z DTEND:20170727T110000Z DTSTAMP:20260414T144605Z UID:session/Rhj8MNzNAHsLSEK9D7aH8L@hasgeek.com SEQUENCE:0 CREATED:20170712T094249Z DESCRIPTION:\n LAST-MODIFIED:20170723T172704Z LOCATION:Auditorium - MLR Convention Centre\, Whitefield\nBengaluru\, \nIN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com BEGIN:VALARM ACTION:display DESCRIPTION:Evening beverage break (auditorium) in Auditorium in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Off The Record (OTR) session: "Fairness\, Accountability and Trans parency (FAT) in ML." DTSTART:20170727T104000Z DTEND:20170727T114000Z DTSTAMP:20260414T144605Z UID:session/B88nZofJ7aFHqBAdMNfzAe@hasgeek.com SEQUENCE:0 CREATED:20170519T052722Z DESCRIPTION:\n LAST-MODIFIED:20170727T072134Z LOCATION:Banquet hall - MLR Convention Centre\, Whitefield\nBengaluru\, \n IN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com BEGIN:VALARM ACTION:display DESCRIPTION:Off The Record (OTR) session: "Fairness\, Accountability and T ransparency (FAT) in ML." in Banquet hall in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Machine Learning: from practice to production. DTSTART:20170727T110000Z DTEND:20170727T114500Z DTSTAMP:20260414T144605Z UID:session/Pk7VdzM48EwgMeJJ7DjvvV@hasgeek.com SEQUENCE:2 CATEGORIES:Full talk for data engineering track,Beginner CREATED:20170712T081634Z DESCRIPTION:### Introduction [2-3 mins]\n\nA short introduction to the top ics that are to be covered. Additional context about the machine learning problems in the domain of ecommerce data will be presented. This section s ets the stage for discussing the machine learning “pipeline” to be bui lt for solving the various problems.\n\n---\n\n### Let there be data [10 m ins]\n\nHaving high-fidelity datasets is crucial when starting on any mach ine learning problem. Balanced classes\, representative coverage of ground truth\, and adversarial examples\, all need to be considered before jumpi ng in with the modelling.\n\n**Garbage in\, garbage out**\n\n_Do I have a reliable source of data? Where do I obtain my dataset?_\n\n**Transforming data to input**\n\n_What pre-processing steps are required? How do I norma lize my data before using with my algorithms?_\n\n---\n\n### Building mode ls [10 mins]\n\nOnce the datasets have been prepared\, the actual “fun ” can begin - experimentation is the name of the game. This section will be present an overview of the landscape together with processes that help weigh available options.\n\n**Now\, let's begin?**\n\n_Which approach do I start with? Are data exploration and visualizations techniques important \, or can I just treat my whole system as a blackbox?_\n\n**Building model s**\n\n_Should I formulate this as classification\, regression or somethin g else? Do random forests still work\, or should I try SVMs or deep neural networks?_\n\n---\n\n### Deploying to production [10 mins]\n\nThe 99.8% a ccurate model is not of much use\, unless it can be integrated into system s meant to solve the actual problem. By constantly keeping these integrati on goals within sight\, the aim is to convey the point that _early and goo d enough_ is often better than _late and perfect_. \n\n**No system is an i sland**\n\n_Do I need to make batched or real-time predictions? Embedded m odels or interfaces? RPC or REST?_\n\n**Monitoring performance**\n\n_How d o I keep track of my predictions? Do I log my results to a database? What about online learning?_\n\n---\n\n### Conclusion [2-3 mins]\n\nWhile pushi ng the state-of-the-art in machine learning might sound interesting\, it i s still important to maintain focus on its applicability within desired do mains. Together with an overview of the points covered\, a few concluding remarks will be presented.\n\n---\n\n![flow](http://i.imgur.com/p3on6BE.pn g)\n\n### Speaker bio\n\nI am a member of the data science team at [Semant ics3](https://www.semantics3.com) - building data-powered software for eco mmerce-focused companies. Over the years\, I have had the chance to dabble in various fields covering data processing\, pipeline setup\, database ma nagement and data science. When not picking locks\, or scuba diving\, I us ually blog about my technical adventures at our [team’s engineering blog ](https://engineering.semantics3.com/@ramananb).\n LAST-MODIFIED:20230810T072606Z LOCATION:Auditorium - MLR Convention Centre\, Whitefield\nBengaluru\, \nIN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com URL:https://hasgeek.com/fifthelephant/2017/schedule/machine-learning-from- practice-to-production-Pk7VdzM48EwgMeJJ7DjvvV BEGIN:VALARM ACTION:display DESCRIPTION:Machine Learning: from practice to production. in Auditorium i n 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Flash talks: presentations by the audience DTSTART:20170727T114000Z DTEND:20170727T121000Z DTSTAMP:20260414T144605Z UID:session/Y4KinjBRqpkpnkUUw914NB@hasgeek.com SEQUENCE:0 CREATED:20170722T145458Z DESCRIPTION:\n LAST-MODIFIED:20170724T025217Z LOCATION:Banquet hall - MLR Convention Centre\, Whitefield\nBengaluru\, \n IN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com BEGIN:VALARM ACTION:display DESCRIPTION:Flash talks: presentations by the audience in Banquet hall in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Off The Record (OTR) session: "Data science in production." DTSTART:20170727T114500Z DTEND:20170727T124500Z DTSTAMP:20260414T144605Z UID:session/WX7GqciRfRYgwvowkBq5cj@hasgeek.com SEQUENCE:0 CREATED:20170712T075512Z DESCRIPTION:\n LAST-MODIFIED:20170723T172712Z LOCATION:Auditorium - MLR Convention Centre\, Whitefield\nBengaluru\, \nIN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com BEGIN:VALARM ACTION:display DESCRIPTION:Off The Record (OTR) session: "Data science in production." in Auditorium in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:The Fifth Elephant 2017 and Anthill Inside 2017 "Networking Data S cientist dinner." DTSTART:20170727T124500Z DTEND:20170727T163000Z DTSTAMP:20260414T144605Z UID:session/VBAm7UwbJTy5rhWmVGfVpr@hasgeek.com SEQUENCE:0 CREATED:20170519T052952Z DESCRIPTION:\n LAST-MODIFIED:20170722T164711Z LOCATION:Bangalore ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com BEGIN:VALARM ACTION:display DESCRIPTION:The Fifth Elephant 2017 and Anthill Inside 2017 "Networking Da ta Scientist dinner." in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Check-in and breakfast DTSTART:20170728T024500Z DTEND:20170728T040000Z DTSTAMP:20260414T144605Z UID:session/JnJkPEZx6xzFKVnHGV8FXA@hasgeek.com SEQUENCE:0 CREATED:20170519T053034Z DESCRIPTION:\n LAST-MODIFIED:20170720T113938Z LOCATION:Bangalore ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com BEGIN:VALARM ACTION:display DESCRIPTION:Check-in and breakfast in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Stretching session DTSTART:20170728T040000Z DTEND:20170728T041000Z DTSTAMP:20260414T144605Z UID:session/Qda2N7hqcnsKTxaYRYEzVk@hasgeek.com SEQUENCE:0 CREATED:20170519T053533Z DESCRIPTION:\n LAST-MODIFIED:20170724T123209Z LOCATION:Banquet hall - MLR Convention Centre\, Whitefield\nBengaluru\, \n IN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com BEGIN:VALARM ACTION:display DESCRIPTION:Stretching session in Banquet hall in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Interactive data visualisation using Markdown. DTSTART:20170728T040000Z DTEND:20170728T044500Z DTSTAMP:20260414T144605Z UID:session/8aXa7jVL2EySqCrhWV8s37@hasgeek.com SEQUENCE:2 CATEGORIES:Full talk for data engineering track,Beginner CREATED:20170712T081443Z DESCRIPTION:**Grammar of interactive graphics: The four layers of abstract ion**\n\n- Data layer: Data types and transformations\n- Visual layer: Var iable mapping\, marks\, channels\, scales\, coordinate system\, and layout s\n- Annotation layer: Titles\, axes\, legends\, grids\, references\, and text\n- Interaction layer: Navigation\, transition\, selection\, highlight ing\, filtering\, brushing and linking\, and sorting\n\n**Using a Declarat ive Grammar based Tool**\n\n- The tools landscape: charting-based\, gramma r-based\, and pixel-based\n- Making interactive graphics - Graphical\, Imp erative and Declarative tools\n- Creating a static visualization (using Vi sdown)\n\n**Visualizing a multidimensional dataset**\n\n- Playing with mar ks\, channels\, color\, scales\, and coordinates\n- Adding labeling and an notation\n- Adding an interaction layer\n\n**Adding interactive data-model manipulation**\n\n- Exploring common interaction patterns: Select\, explo re\, reconfigure\, encode\, filter\, and drill-down\n- Creating an interac tive data visualization\n\n**Building your own declarative visualisation t ools**\n\n- Approach to building Visdown and lessons learnt\n- Adopting an d building declarative based tools in your domain / workflow\n\n### Speake r bio\n\nAmit Kapoor is interested in learning and teaching the craft of t elling visual stories with data. He is the founder partner at narrativeVIZ Consulting\, where he teaches data-science\, data-visualisation and data- stories as tools for improving communication\, persuasion\, and leadership and conducts workshops on these topics for businesses\, nonprofits\, and academic institutes. You can find more about him at http://amitkaps.com an d tweet him at [@amitkaps](http://twitter.com/amitkaps).\n LAST-MODIFIED:20230810T072606Z LOCATION:Auditorium - MLR Convention Centre\, Whitefield\nBengaluru\, \nIN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com URL:https://hasgeek.com/fifthelephant/2017/schedule/interactive-data-visua lisation-using-markdown-8aXa7jVL2EySqCrhWV8s37 BEGIN:VALARM ACTION:display DESCRIPTION:Interactive data visualisation using Markdown. in Auditorium i n 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Bits and joules: data-driven energy systems. DTSTART:20170728T041000Z DTEND:20170728T045500Z DTSTAMP:20260414T144605Z UID:session/ReYmNcoMaAgZYZ9PiLytof@hasgeek.com SEQUENCE:2 CATEGORIES:Full talk for Data in Government track ,Beginner CREATED:20170725T051521Z DESCRIPTION:The electricity industry is going through a paradigm shift by moving from centralised generation to distributed energy resources. This t alk will give an overview of this shift\, discuss how data-driven energy s ystems are powering this shift\, and illustrate the approach through a spe cific use case of solar plant management. I will also provide some pointer s for exploring the space.\n\n### Speaker bio\n\nDeva recently co-founded DataGlen\, a company focused on enabling Distibuted Energy Resources throu gh IoT and big data technologies. Prior to this\, he founded and led the S marter Energy Systems group for IBM Research India. The work done by his g roup and him were recognised with MIT TR 35 and Indian National Academy of Engineering awards. He has also won best paper awards in top research con ferences such as ACM e-Energy and ACM BuildSys.\n\nPrior to IBM\, he led F rance Telecom's pervasive media research group in Boston. On the entrepren eurial side\, he co-founded RadioSherpa\, a company that developed innovat ive HD Radio technologies and applications\, and he was instrumental in se lling the company to TuneIn Inc\, a Google ventures company. \n\nHis vario us projects have been covered by prominent media outlets such as Boston Gl obe\, BBC\, IEEE Spectrum\, MIT Technology Review\, New Scientist\, Scient ific American\, Slashdot and Wired. He has 11 granted US patents and has p ublished more than 50 papers in top research conferences.\n LAST-MODIFIED:20230810T072606Z LOCATION:Banquet hall - MLR Convention Centre\, Whitefield\nBengaluru\, \n IN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com URL:https://hasgeek.com/fifthelephant/2017/schedule/bits-and-joules-data-d riven-energy-systems-ReYmNcoMaAgZYZ9PiLytof BEGIN:VALARM ACTION:display DESCRIPTION:Bits and joules: data-driven energy systems. in Banquet hall i n 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:What explains our marks? DTSTART:20170728T044500Z DTEND:20170728T050500Z DTSTAMP:20260414T144605Z UID:session/XKSaaVHHxwZwmuKzD4g2s9@hasgeek.com SEQUENCE:2 CATEGORIES:Crisp talk for Data in Government track,Beginner CREATED:20170712T081511Z DESCRIPTION:Slides are at https://learn.gramener.com/downloads/talks/2017- 05-24-NAS-Autolysis.pptx\n\n### Speaker bio\n\nAnand is a co-founder of Gr amener\, a data science company. He leads a team of data enthusiasts with skills in analysis\, design\, programming and statistics.\n\nHe studied at IIT Madras\, IIM Bangalore and LBS\, and worked at IBM\, Infosys\, Lehman Brothers and BCG. He and his team explore insights from data and communic ate these as visual stories.\n LAST-MODIFIED:20230810T072606Z LOCATION:Auditorium - MLR Convention Centre\, Whitefield\nBengaluru\, \nIN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com URL:https://hasgeek.com/fifthelephant/2017/schedule/what-explains-our-mark s-XKSaaVHHxwZwmuKzD4g2s9 BEGIN:VALARM ACTION:display DESCRIPTION:What explains our marks? in Auditorium in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Do you know what's on TV? DTSTART:20170728T045500Z DTEND:20170728T054000Z DTSTAMP:20260414T144605Z UID:session/4nMGRADM7TqPcEEdMiFApa@hasgeek.com SEQUENCE:2 CATEGORIES:Full talk for data engineering track,Intermediate CREATED:20170712T081325Z DESCRIPTION:**Do you know what's on TV?**\n\n\n**What is TV and where is i t headed?**\n\nA quick preview.\n\nTV is about the content you see on the screen. It is in two forms: Linear TV (the TV you get from Satellite or Ca ble) and Non-Linear TV (the TV you get On Demand\, largely from the Intern et). \n\nLinear TV is still going strong if you consider its large numbers - although in some parts of the world they say Non-Linear TV is eating in to TV.\n\nThere are some analogies you can draw between them. \n\nLinear T V is like Mumbai Local Train system. It runs on its own. Large masses of p eople get in and get out.\n\nNon-Linear TV is like an Uber or Ola. You hai l for a Taxi. There's one just for you. You get in and get out at your des tination\, at your time and at your place.\n\nNow\, will Uber and Ola repl ace the Mumbai Local Train System? Never. It simply wont scale for those n umbers. But both will co-exist.\n\nYou should expect TV to co-exist\, and even better become Hybrid.\n\nNon-Linear TV has merely taken the place of DVD Players. Those DVDs are gone. They are all in the Cloud now\, and comi ng in wires over the Internet.\n\n\n**The Linear TV world was designed for a world devoid of the Internet**\n\nYou have entire stacks of technology that did not assume any Internet. Broadcasters acquired content licenses\, actual tapes\, and then transmitted "streaming" content to satellite\, th at was then collected using dish farms\, and transmitted over wires to hom es - to be then decrypted and shown on TV.\n\nAs a consumer\, you'd always consume content through a Set-top Box\, that had no return passage\, and was not a connected device. There was no reason to.\n\nWith Hybrid TV comi ng in\, you'll soon see Set-top Boxes or TVs themselves allow you to consu mer both Linear and Non-Linear TV together. These boxes are going to be "c onnected" to the Internet\, and can send back data about what is being wat ched.\n\nImagine\, something you always had over the Internet. The ability to find out which unique user just visited a page - has never been availa ble to the largest medium of information delivery. And that is all about t o change.\n\nYou'll have millions of boxes ready to transmit data back abo ut what is being watched. But is the TV industry ready to do things with t hat data?\n\n\n**Connected Linear TV opens many doors**\n\nImagine a syste m that knew:\n\n- The channel you just saw.\n- The ads you did not switch away from.\n- The actors you did not miss when you watched a movie on TV.\ n- The songs you waited for\, even if you had to go past an ad break.\n- T he news topics you track.\n\nNot at Internet scale\, but at TV scale.\n\nH ere are some business usecases:\n\nTV Synchronized Advertising: Ads (or fo llow on ads) that show up on your mobile\, as soon as you've seen the same ad on TV.\n\nCelebrity Apparel: Ways to shop for apparel worn by celebrit ies that just came on TV.\n\nAdvertising Measurement: The exact people (or their stereotypes) that watched an ad on TV.\n\nTo do all this\, we first need to know "What exactly is on TV?"\n\n**The state of metadata on Linea r TV**\n\nThe EPG (Electronic Program Guide) is as good you get right now. The EPG describes what Show is on which channel. You'll probably get more metadata about the Show itself\, the actors\, the duration\, and so on. B ut there's no available data on:\n\n- What ads just played?\n- Which House Promotion just played?\n- Are we in an Ad Break?\n- Which actor is on scr een?\n- What was just said on TV?\n\nYou cannot wait for Broadcasters to g ive you this data. A lot of technology needs to change for that.\n\nThe wo rld is about to need them all. So\, let's start reverse engineering this d ata.\n\n\n**So\, what exactly is Linear TV made up of?**\n\nLinear TV look s like this (if you allow me to use a regular expression):\n\n(ContentSegm ent . BreakMarker? . (Ad|HousePromo)+ . BreakMarker? ContentSegment)+\n\nT he EPG you get largely tags the Content Segment\, but wont tell when the A d breaks.\n\nBut no body is going to tell you about BreakMarker\, Ad\, Hou sePromo etc. There is no database to look up. No standards or compliance. No watermarks (at least those that are accessible to third parties).\n\n\n **Goal: Can we figure out ContentSegment . BreakMarker. Ad . HousePromo .* *\n\nLook at TV as continuous streaming video: 60 fps pictures + aligned a udio + EPG metadata.\n\nAre there patterns that we can employ to unearth t hese segments\, and tag them appropriately?\n\nHere are some heuristics:\n \nBreak Markers: Signature sequences of video or audio that are specific t o a channel\, and/or a show. If they signatures that belong to a show\, th ey always come along with the show\, and very seldom else where. They are also sentinels that separate the content from the ads.\n\nAds: Ads are sho rt. Ads are heavy on audio. Ads repeat a lot. Ads occur across channels. A ds always come together.\n\nHouse Promos: House Promos come with Ads. [Thi s kind of makes them hard to distinguish]. House promos feature actors tha t are regular in the Show. This is unlike Ads.\n\nSo\, let's start mining for clips - that repeat a lot in TV. A clip is a maximal sequence of audio /video that occurs intact\, and repeats many times on TV.\n\nThis is maxim al sequence mining problem. NP(Hard). We need to make it more efficient. L et's do it in audio first. Audio can be converted to numbers - using finge rprinting algorithms (references).\n\nA temporal reverse index is built\, and used to mine for repeating sequences of audio. \n\nNot all audio repet itions are true clips. Eg: Fake laughter. Background music.\nDifferent aud io clip candidates could be slight alterations of each other. Eg: Variants of ads.\n\nContinue the processing in video domain\, by creating a more c onstrained set of candidates around audio candidates.\n\nAfter candidate c lips are obtained\, "score" them - to label them as break markers\, ads or house promos.\n\n\n**Demo of the whole system in action:**\n\nAdBreaks.in tags ads in real time on Linear TV. I'll show the audience how audio cand idates are generated\, how we generate video candidates from them\, and fu rther get clips to the exact frame. Will further show how break markers an d house promos are classified.\n\nAlongside\, I'll also demo use cases whe re AdBreaks.in has been used.\n\n1) TV Ad Research.\n2) TV Ad Playout Moni toring. TV Synchronized Advertising.\n3) Dynamic Ad Replacement in OTT str eams. [A collaboration with Amagi]\n\n**The road ahead:**\n\n- Language-in dependent Hot keyword detection in news.\n- Celebrity frames\, and detecti on of clothing.\n- Linear TV segmentation for Catch Up TV.\n\n### Speaker bio\n\nBharath Mohan loves to study how information flows through society - and create products that make the right information get to the right peo ple. He got his PhD on this topic at IISc\, Bangalore - mining for nurture rs among computer science researchers. He then went on to work at Google N ews - studying how news starts off from an original source\, and is quickl y copied or re-hashed by several publishers across the world. He’s been doing startups over the last few years\, and the latest one Sensara.TV is about unraveling Television.\n LAST-MODIFIED:20230810T072606Z LOCATION:Banquet hall - MLR Convention Centre\, Whitefield\nBengaluru\, \n IN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com URL:https://hasgeek.com/fifthelephant/2017/schedule/do-you-know-whats-on-t v-4nMGRADM7TqPcEEdMiFApa BEGIN:VALARM ACTION:display DESCRIPTION:Do you know what's on TV? in Banquet hall in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Maps ❤️ Data: a voyage across the world of geo-visualization. DTSTART:20170728T050500Z DTEND:20170728T055000Z DTSTAMP:20260414T144605Z UID:session/JAT8Jdq86PHa6qF9qodNGW@hasgeek.com SEQUENCE:2 CATEGORIES:Full talk for data engineering track,Intermediate CREATED:20170712T081458Z DESCRIPTION:This talk aims at reflecting back at cartography practices ove r the centuries\, and possibilities of visualizing data on maps with the t oday’s tools. Inspired by the survey format of the seminal paper titled _“A tour through the visualization zoo”_ by Heer et al\, I plan to cov er a variety of types of geo-visualizations\, accompanying each category w ith an explanation on what data suits it best\, and tips on designing it.\ n\nSpecifically\, I plan to cover:\n\n- Showing data _in a map_ (Manipulat ing map layers)\n- Showing data _on a map_ (Overlaying data as a visualiza tion layer on a map)\n- Showing data as a _non-geographic map_ (Visualizat ions that may not be geographically accurate\, like cartograms and isoplet hs)\n- Showing geographic data _without a map_ (Like using parallel coordi nates to show flow across geographic locations)\n\nThe talk will wrap-up w ith a short discussion on the tools that one can use today to build these. \n\n### Speaker bio\n\nRasagy Sharma works as a designer at Mapbox\, where he helps build tools to improve the biggest geo-spatial open data project : OpenStreetMap\, and explores custom map design & data visualizations. Be fore this\, he worked as a UX Designer at Barclays\, helped kickstart the Information Design Lab at IDC\, IIT Bombay\, and worked with the Cloud & E nterprise and Bing Sports team at Microsoft IDC\, Hyderabad. He’s intere sted in Data Art and loves playing with code.\n LAST-MODIFIED:20230810T072606Z LOCATION:Auditorium - MLR Convention Centre\, Whitefield\nBengaluru\, \nIN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com URL:https://hasgeek.com/fifthelephant/2017/schedule/maps-%5B%3F%5D-data-a- voyage-across-the-world-of-geo-visualization-JAT8Jdq86PHa6qF9qodNGW BEGIN:VALARM ACTION:display DESCRIPTION:Maps ❤️ Data: a voyage across the world of geo-visualizati on. in Auditorium in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Morning beverage break (banquet) DTSTART:20170728T054000Z DTEND:20170728T061000Z DTSTAMP:20260414T144605Z UID:session/7QnZxcxvcwwE71k8Nr3ZHL@hasgeek.com SEQUENCE:0 CREATED:20170519T053604Z DESCRIPTION:\n LAST-MODIFIED:20181212T065504Z LOCATION:Banquet hall - MLR Convention Centre\, Whitefield\nBengaluru\, \n IN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com BEGIN:VALARM ACTION:display DESCRIPTION:Morning beverage break (banquet) in Banquet hall in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Morning beverage break (auditorium) DTSTART:20170728T055000Z DTEND:20170728T062000Z DTSTAMP:20260414T144605Z UID:session/Ti3qWN1QKyQg5sx6Re2mZC@hasgeek.com SEQUENCE:0 CREATED:20170519T054353Z DESCRIPTION:\n LAST-MODIFIED:20181212T065510Z LOCATION:Auditorium - MLR Convention Centre\, Whitefield\nBengaluru\, \nIN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com BEGIN:VALARM ACTION:display DESCRIPTION:Morning beverage break (auditorium) in Auditorium in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Designing ML pipelines for mining transactional SMS messages DTSTART:20170728T061000Z DTEND:20170728T065500Z DTSTAMP:20260414T144605Z UID:session/5jAfLfiyCHrk2sGeSiBVNW@hasgeek.com SEQUENCE:2 CATEGORIES:Full talk for data engineering track,Intermediate CREATED:20170712T080146Z DESCRIPTION:1) Introduction to data science problems where transforming ra w data into features itelf requires statistical modeling and the example c ase of transactional SMS messages.\n\n2) The creative process of represent ing a complex domain of the world (like personal finance) with concepts an d features that can be mapped to data.\n\n3) Building machine learning mod els to solve the problems defined in step 2 and designing an architecture to run the models in extensible and auditable pipelines.\n\n*/ Each part o f the talk will include detailed examples and technical content */\n\n### Speaker bio\n\nPaul Meinshausen is a globally experienced data scientist. He is a Co-Founder of PaySense\, a mobile fintech startup based in Mumbai\ , and was Chief Data Officer at the company until February 2017. Before co -founding PaySense\, Paul was Vice President of Data Science at Housing.co m\, where he led the Data Science Lab and the Product Analytics and Busine ss Intelligence teams. Earlier he was Principal Data Scientist at Teradata \, where he worked on machine learning projects in the Banking\, Telecom\, Automotive\, and E-Commerce industries across the South Asia and APAC reg ions. Paul was a Data Science for Social Good Fellow at the Computation In stitute at the University of Chicago in 2013. Between 2009 and 2011 he ser ved as an analyst for the U.S. Department of the Army and deployed to Kabu l\, Afghanistan to the headquarters of the International Security Assistan ce Force in Afghanistan. Paul has an academic research background in behav ioral science and was a researcher in the Department of Psychology at Harv ard University and a Fulbright Scholar in Turkey at the Middle East Techni cal University.\n LAST-MODIFIED:20230810T072606Z LOCATION:Banquet hall - MLR Convention Centre\, Whitefield\nBengaluru\, \n IN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com URL:https://hasgeek.com/fifthelephant/2017/schedule/designing-machine-lear ning-pipelines-for-mining-transactional-sms-messages-5jAfLfiyCHrk2sGeSiBVN W BEGIN:VALARM ACTION:display DESCRIPTION:Designing ML pipelines for mining transactional SMS messages i n Banquet hall in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Stretching session DTSTART:20170728T062000Z DTEND:20170728T063000Z DTSTAMP:20260414T144605Z UID:session/QkWJgmFps691n54SYUkFri@hasgeek.com SEQUENCE:0 CREATED:20170722T162650Z DESCRIPTION:\n LAST-MODIFIED:20170724T123217Z LOCATION:Auditorium - MLR Convention Centre\, Whitefield\nBengaluru\, \nIN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com BEGIN:VALARM ACTION:display DESCRIPTION:Stretching session in Auditorium in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Off The Record (OTR) session: "Data Visualization." DTSTART:20170728T063000Z DTEND:20170728T071500Z DTSTAMP:20260414T144605Z UID:session/TUuUv98iYQNfVFDjRkpbRi@hasgeek.com SEQUENCE:0 CREATED:20170712T100803Z DESCRIPTION:\n LAST-MODIFIED:20170723T061602Z LOCATION:Room 1 - MLR Convention Centre\, Whitefield\nBengaluru\, \nIN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com BEGIN:VALARM ACTION:display DESCRIPTION:Off The Record (OTR) session: "Data Visualization." in Room 1 in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Off The Record (OTR) session: "Finance data analytics." DTSTART:20170728T063000Z DTEND:20170728T071500Z DTSTAMP:20260414T144605Z UID:session/7hmU6Sk3qdwCJiYrpgEXmz@hasgeek.com SEQUENCE:0 CREATED:20170723T061557Z DESCRIPTION:\n LAST-MODIFIED:20170723T061921Z LOCATION:Auditorium - MLR Convention Centre\, Whitefield\nBengaluru\, \nIN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com BEGIN:VALARM ACTION:display DESCRIPTION:Off The Record (OTR) session: "Finance data analytics." in Aud itorium in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Q&A with presenters on use cases DTSTART:20170728T065500Z DTEND:20170728T071500Z DTSTAMP:20260414T144605Z UID:session/MbXmE1xQKWzsqQ29pdJDqa@hasgeek.com SEQUENCE:0 CREATED:20170722T161621Z DESCRIPTION:\n LAST-MODIFIED:20170723T072711Z LOCATION:Banquet hall - MLR Convention Centre\, Whitefield\nBengaluru\, \n IN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com BEGIN:VALARM ACTION:display DESCRIPTION:Q&A with presenters on use cases in Banquet hall in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Gabbar: Machine learning to guard OpenStreetMap DTSTART:20170728T071500Z DTEND:20170728T080000Z DTSTAMP:20260414T144605Z UID:session/FvXCCc8dEkB3Zh4mLrCqhE@hasgeek.com SEQUENCE:2 CATEGORIES:Full talk for data engineering track,Intermediate CREATED:20170712T081714Z DESCRIPTION:*Edits in a few minutes on OpenStreetMap*\n\n![50pbxyi-scaled] (https://cloud.githubusercontent.com/assets/2899501/25565959/d5798a44-2dee -11e7-950d-a28a110c3791.gif)\n\n##### 1. OpenStreetMap (OSM)\n- OSM is the largest free and open map of the world\, the Wikipedia of maps.\n- On a t ypical day\, 2 million features are created\, half a million modified and a quarter features deleted.\n\n##### 2. Validation\n- The OSM community\, the heart beat of OpenStreetMap.\n- Interesting problems and inherent chal lenges.\n\n##### 3. Tools\n- OpenStreetMap changeset analyzer: https://osm cha.mapbox.com/\n- Rule based validation with: https://github.com/mapbox/o sm-compare\n\n##### 4. Gabbar\n- Guarding OSM from invalid or suspicious e dits.\n- Machine learning based infrastructure collaboratively build in th e open.\n- Development workflow with Python data science tools.\n- Learnin g’s\, current model performance and impact.\n\n##### 5. Future\n- Using AI to help make OSM the best map of the world!\n- Using open collaborative machine learning for open collaborative projects.\n\n### Speaker bio\n\nH ey\, I am Bhargav Kowshik\, a Software Engineer at Mapbox\, Bengaluru. I b uild tools to scale data operations at Mapbox. I am passionate about peopl e and communities\, open data and technology\, creativity and side project s. Previously as the first engineer at Nextdrop\, I helped build a platfor m to track water availability and consumption. You can contact me at:\n\n- https://twitter.com/bkowshik/\n- https://github.com/bkowshik/\n LAST-MODIFIED:20230810T072606Z LOCATION:Auditorium - MLR Convention Centre\, Whitefield\nBengaluru\, \nIN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com URL:https://hasgeek.com/fifthelephant/2017/schedule/guarding-osm-from-inva lid-edits-with-gabbar-FvXCCc8dEkB3Zh4mLrCqhE BEGIN:VALARM ACTION:display DESCRIPTION:Gabbar: Machine learning to guard OpenStreetMap in Auditorium in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Lunch break (banquet hall) DTSTART:20170728T071500Z DTEND:20170728T081500Z DTSTAMP:20260414T144605Z UID:session/B2JuTTsnrCbtpaXhnYkdBK@hasgeek.com SEQUENCE:0 CREATED:20170519T053830Z DESCRIPTION:\n LAST-MODIFIED:20170722T161653Z LOCATION:Banquet hall - MLR Convention Centre\, Whitefield\nBengaluru\, \n IN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com BEGIN:VALARM ACTION:display DESCRIPTION:Lunch break (banquet hall) in Banquet hall in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Lunch break (auditorium) DTSTART:20170728T080000Z DTEND:20170728T090000Z DTSTAMP:20260414T144605Z UID:session/VVbsPyewNmrHanR8RH4BJR@hasgeek.com SEQUENCE:0 CREATED:20170712T094535Z DESCRIPTION:\n LAST-MODIFIED:20170722T150032Z LOCATION:Auditorium - MLR Convention Centre\, Whitefield\nBengaluru\, \nIN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com BEGIN:VALARM ACTION:display DESCRIPTION:Lunch break (auditorium) in Auditorium in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Off The Record (OTR) session: "Worst disaster stories in ML." DTSTART:20170728T081500Z DTEND:20170728T090000Z DTSTAMP:20260414T144605Z UID:session/YVh4HPB28CyoGfqx8YsBQn@hasgeek.com SEQUENCE:0 CREATED:20170519T052515Z DESCRIPTION:\n LAST-MODIFIED:20170723T171312Z LOCATION:Room 1 - MLR Convention Centre\, Whitefield\nBengaluru\, \nIN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com BEGIN:VALARM ACTION:display DESCRIPTION:Off The Record (OTR) session: "Worst disaster stories in ML." in Room 1 in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:How we are building serverless architectures for Deep Learning and NLP at Episource. DTSTART:20170728T081500Z DTEND:20170728T083500Z DTSTAMP:20260414T144605Z UID:session/JX9F8Em6nw3uf21wHqvkaM@hasgeek.com SEQUENCE:2 CATEGORIES:Crisp talk for data engineering track,Intermediate CREATED:20170722T161942Z DESCRIPTION:- Problems & Challenges\n- Why Serverless ?\n- Components of t his serverless NLP architecture\n- Towards an immutable configuration \n- Architecture Diagram & Details\n- Impact of the serverless architecture\n- Demo\n\nThe slides link has been shared\, and will be updated regularly.\ n\n### Speaker bio\n\nI am currently leading the NLP & Data Science practi ce at Episource\, a US healthcare company. My daily work revolves around w orking on semantic technologies and computational linguistics (NLP)\, buil ding algorithms and machine learning models\, researching data science jou rnals and architecting secure product backends in the cloud.\n\nTechstack that my team and I typically work on includes\;\n\nLanguage: Python\nTesti ng Frameworks: unittest\, pytest\nAutomation & Configuration Management: A nsible\, Docker\, Vagrant\nCI: Travis CI\nCloud Services: AWS\, Google Clo ud\, MS Azure\nAPIs: Bottle\, CherryPy\, Flask\nDatabases: MySQL\, SQLite\ , MSSQL\, RDF stores\, Neo4J\, ElasticSearch\, MongoDB\, Redis\nEditor: Su blime\, Pycharm\n\nI have architected multiple commercial NLP solutions in the area of healthcare\, foods & beverages\, finance and retail. I am dee ply involved in functionally architecting large scale business process aut omation & deep insights from structured & unstructured data using Natural Language Processing & Machine Learning. I have contributed to multiple NLP libraries like Gensim and Conceptnet5. I blog regularly on NLP on multipl e forums like Data Science Central\, LinkedIn and my blog NLP Wave. \n\nI love teaching and mentoring students. I speak regularly on NLP and text an alytics at conferences and meetups like Pycon India and PyData. I have als o taught multiple hands-on session at IIM Lucknow and MDI Gurgaon. I have mentored students from schools like ISB Hyderabad\, BITS Pilani\, Madras S chool of Economics. When bored - I like to fall back on Asimov to lead me into an alternate reality.\n LAST-MODIFIED:20230810T072606Z LOCATION:Banquet hall - MLR Convention Centre\, Whitefield\nBengaluru\, \n IN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com URL:https://hasgeek.com/fifthelephant/2017/schedule/how-we-are-building-se rverless-architectures-for-deep-learning-nlp-at-episource-JX9F8Em6nw3uf21w HqvkaM BEGIN:VALARM ACTION:display DESCRIPTION:How we are building serverless architectures for Deep Learning and NLP at Episource. in Banquet hall in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Plumbing data science pipelines. DTSTART:20170728T083500Z DTEND:20170728T085500Z DTSTAMP:20260414T144605Z UID:session/9LibNHdd7a4tWoQaFoCQUN@hasgeek.com SEQUENCE:2 CATEGORIES:Crisp talk for data engineering track,Intermediate CREATED:20170722T162000Z DESCRIPTION:The talk begins with a brief of Machine Learning and the commo n problems faced. Then we progress further to explain how we tackled the m achine learning problem using celery pipelines and monitoring strategies. \n\nThere will be a basic showcase from our ETL workflow and some dashboar ds to explain monitoring using the ELK stack (Elasticsearch\, Logstash\,Ki bana) and Monit.\n\nWe will be learning and understanding the performances of the following tech stack. \n\nCelery\nRabbitMQ\nSimple Queue Service ( SQS)\nElastic Cache (Redis)\nAWS technologies - Redshift\, S3\nELK Stack ( Elastic Search\, Logstash\, Kibana)\n\n### Speaker bio\n\nKrishnapriya (KP ) is a hardcore Data Engineer with over 5 years of experience in the Data Engineering Space and the AWS stack. At Mad Street Den\, she is part of th e data science team and works closely with Data Scientists to build cost-e ffective cutting edge data products. She enables them to get their hands o n all kinds of data sources in different forms and fidelities using scalab le and robust data pipelines and workflows.\n LAST-MODIFIED:20230810T072606Z LOCATION:Banquet hall - MLR Convention Centre\, Whitefield\nBengaluru\, \n IN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com URL:https://hasgeek.com/fifthelephant/2017/schedule/plumbing-data-science- pipelines-9LibNHdd7a4tWoQaFoCQUN BEGIN:VALARM ACTION:display DESCRIPTION:Plumbing data science pipelines. in Banquet hall in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Governance using Apache Atlas: why and how. DTSTART:20170728T085500Z DTEND:20170728T092500Z DTSTAMP:20260414T144605Z UID:session/HhEqfDpcYdze6AertvbE7v@hasgeek.com SEQUENCE:2 CATEGORIES:Full talk for data engineering track,Intermediate CREATED:20170712T081901Z DESCRIPTION:Apache Atlas Project Introduction\nData Governance challenge a nd use case scenarios\nAtlas architechture\nArchitechture choices : Pros a nd cons\nCross component lineage capability of Atlas\nApache Ranger integr ation to enforce tag based policies\nAtlas TypeSystem\nModel a popular Had oop component for Atlas\nDemo based on the above model\nFuture/Roadmap\nIn vitation to contribute\n\nMore details on Order of presentation\n\nWhy Apa che Atlas(What are the use cases)\nEnterprises have 100s of ETL pipelines wherein developers take the source data\, apply transformations and persis t the result into the warehouse. Now\, if an upstream pipeline breaks/fail s\, how does the owner of current dataset narrow down on the cause and cul prit ETL pipeline. Further\, if the current pipeline breaks\, the owner ha s no mechanism to alert the owners of downstream processes. A tool which c ould keep track of the provenance/lineage/impact of a dataset would solve this issue. Atlas has the capability to track lineage of the datasets.\n\n ETL redundancy is another striking issue in current enterprise Hadoop depl oyments. Many developers process data and persist it to the warehouse. The y don't have any mechanism to detect if the result they need is already co mputed and resides in a dataset. Using the lineage diagram and classificat ion feature of Atlas\, developers can look into the details of derived dat asets and skip the expensive processing if the information is already avai lable in one of the derived datasets.\n\nFurther\, enterprises need to adh ere to compliance policies which span multiple datasets across components like Hive\, HBase\, HDFS etc. How can the business make sure that a partic ular policy is enforced across datasets in these components. Datasets can be tagged in Atlas and Ranger can use its Tag based policy feature to enfo rce constraints\n\nCluster admin may need to periodically clean up the unu sed/dormant datasets from the warehouse. How can the admin narrow down on the candidate datasets for archival. Atlas is useful in determining the re levance of a dataset on the basis of the number of tags and downstream dat asets derived from it.\n\n\nWhat is Apache Atlas\nApache Atlas is the gove rnance and metadata framework for Hadoop. Atlas has a scalable and extensi ble architecture which can plug into many Hadoop components to manage thei r metadata in a central repository. By virtue of its extensible TypeSystem \, any arbitrary component(not necessarily a Hadoop component) can be mode lled to capture the metadata of its datasets and events. The metadata even ts can then be classified using tags which can further be used to enforce security policies by Ranger. When a dataset derives from another dataset\, the event can be registered and Atlas will capture the lineage relationsh ip.\n\nHow\nAtlas provides inbuilt support for some Hadoop components like Hive\, Storm and Sqoop. This means that whenever new datasets and events are created in these components\, Atlas captures the metadata of those eve nts. For new components like Spark\, first the model of the metadata to be captured needs to be defined and registered with Atlas. Once the model is in place\, datasets and events occuring in that component can be register ed with Atlas using its rich REST API.\n\nThe demo for the presentation wi ll cover these parts. First\, Spark datasets will be modeled and registere d with Atlas. Then\, a realistic use case will be considered where we will capture a lineage relationship across components like HDFS and Kafka. We will then go to Atlas UI and inspect lineage and other features like tag b ased classification\, search and advanced search\n\n### Speaker bio\n\nVim al Sharma is an Apache Atlas Committer at Hortonworks. Vimal graduated fro m IIT Kanpur with a B.Tech in Computer Science. Vimal is highly passionate about Hadoop stack and has previously worked on scaling backend systems a t WalmartLabs using Spark and Kafka. \n\nVimal was a speaker at ApacheCon BigData 2017 https://apachebigdata2017.sched.com/event/A03h\nVimal regular ly speaks at various events on topics like Apache Atlas\, Apache Spark and Apache Sqoop.\n LAST-MODIFIED:20230810T072606Z LOCATION:Banquet hall - MLR Convention Centre\, Whitefield\nBengaluru\, \n IN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com URL:https://hasgeek.com/fifthelephant/2017/schedule/governance-using-apach e-atlas-why-and-how-HhEqfDpcYdze6AertvbE7v BEGIN:VALARM ACTION:display DESCRIPTION:Governance using Apache Atlas: why and how. in Banquet hall in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Off The Record (OTR) session: "Spark: use cases and challenges in production." DTSTART:20170728T090000Z DTEND:20170728T094500Z DTSTAMP:20260414T144605Z UID:session/3QW4f1yhsAKNHBLZGSJRHW@hasgeek.com SEQUENCE:0 CREATED:20170721T084704Z DESCRIPTION:\n LAST-MODIFIED:20170722T165445Z LOCATION:Room 1 - MLR Convention Centre\, Whitefield\nBengaluru\, \nIN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com BEGIN:VALARM ACTION:display DESCRIPTION:Off The Record (OTR) session: "Spark: use cases and challenges in production." in Room 1 in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:5 Lessons I’ve Learned Tackling Product Matching for E-commerce DTSTART:20170728T090000Z DTEND:20170728T094500Z DTSTAMP:20260414T144605Z UID:session/GcdNP1xEcnzWNBdNWo3cUR@hasgeek.com SEQUENCE:2 CATEGORIES:Full talk for data engineering track,Intermediate CREATED:20170718T130154Z DESCRIPTION:The talk will be framed as questions you should ask yourself w hen you find that you’ve hit a roadblock.\n\n### Part 1 [10-15 mins]\nA checklist of no-brainers and best practices that you should make sure you' ve followed. This will include questions like:\n\n* Have you tried overfit ting your model on a smaller dataset?\n\n* Have you tried training on stan dard corpora (Imagenet etc)?\n\n* Is your dataset balanced\, and if not\, how should you get past this?\n\n* Have you checked where your gradients a nd activation functions are at (through tools like Tensorboard)?\n\n* Have you gotten your hands muddy with the data itself?\n\n[I’ve written abou t this previously here](https://engineering.semantics3.com/2016/10/09/debu gging-neural-networks-a-checklist/).\n\n### Part 2 [20-25 mins]\nDeeper qu estions (no pun intended) to help surface core problems with your dataset\ , your mode of learning or your model. For each question\, I’ll present a scenario where the asking the question helps get past the problem at han d:\n\n* Is your network learning the quirks in your training dataset\, or is it learning to solve the problem at hand? (Helps unearth flaws in the d ataset).\n\n* Is your network incapable or just lazy? If it’s the latter \, how do you force it to learn? (Helps force your network past a local ma xima\, especially when training with multiple inputs).\n\n* Does your netw ork have siblings that can give it a leg-up (through pre-trained weights)? (Helps with scenarios where the problem is complicated to grasp\, or the dataset is poor/sparse).\n\n* Have you tried giving your network training wheels (through feature engineering)? (Helps uncover the benefits of hand- crafting features).\n\n* Never mind a neural network\; can a human with no prior knowledge\, educated on nothing but a diet of your training dataset \, solve the problem? (Helps to understand whether your problem can even b e solved through a representative dataset).\n\n* Is your network looking a t your data through the right lens? (Helps to understand shortcomings in y our pre-processing steps).\n\n[I've written about this previously here](ht tps://blog.semantics3.com/questions-intuition-for-tackling-deep-learning-p roblems-2b3a22b32309)\n\n### Speaker bio\n\nGovind is a co-founder of [Sem antics3](www.semantics3.com). Semantics3 provides Data APIs and AI APIs fo r e-commerce focused companies to make better decisions and grow their bus inesses. We’re a 5-year old Y Combinator backed startup based in Bengalu ru\, San Francisco and Singapore.\n\nOur data-science team\, where my focu s lies\, has been working on e-commerce data problems like product categor ization\, SKU matching\, named entity recognition and unsupervised content extraction for several years.\n LAST-MODIFIED:20230810T072606Z LOCATION:Auditorium - MLR Convention Centre\, Whitefield\nBengaluru\, \nIN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com URL:https://hasgeek.com/fifthelephant/2017/schedule/questions-and-intuitio n-for-tackling-deep-learning-problems-GcdNP1xEcnzWNBdNWo3cUR BEGIN:VALARM ACTION:display DESCRIPTION:5 Lessons I’ve Learned Tackling Product Matching for E-comme rce in Auditorium in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Stretching session DTSTART:20170728T092500Z DTEND:20170728T093500Z DTSTAMP:20260414T144605Z UID:session/WvwM4hQ1eyVUFdepYd5LqN@hasgeek.com SEQUENCE:0 CREATED:20170722T162815Z DESCRIPTION:\n LAST-MODIFIED:20170724T123234Z LOCATION:Banquet hall - MLR Convention Centre\, Whitefield\nBengaluru\, \n IN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com BEGIN:VALARM ACTION:display DESCRIPTION:Stretching session in Banquet hall in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Off The Record (OTR) session: "Securing data stored in the cloud f or big data analysis." DTSTART:20170728T093500Z DTEND:20170728T103500Z DTSTAMP:20260414T144605Z UID:session/FhiS55TrFyvWisYZZDe8kT@hasgeek.com SEQUENCE:0 CREATED:20170712T101706Z DESCRIPTION:\n LAST-MODIFIED:20170726T031651Z LOCATION:Banquet hall - MLR Convention Centre\, Whitefield\nBengaluru\, \n IN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com BEGIN:VALARM ACTION:display DESCRIPTION:Off The Record (OTR) session: "Securing data stored in the clo ud for big data analysis." in Banquet hall in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Stretching session DTSTART:20170728T094500Z DTEND:20170728T095500Z DTSTAMP:20260414T144605Z UID:session/TFZJQFCRc5eQuAGaR3bFxD@hasgeek.com SEQUENCE:0 CREATED:20170722T162731Z DESCRIPTION:\n LAST-MODIFIED:20170724T123238Z LOCATION:Auditorium - MLR Convention Centre\, Whitefield\nBengaluru\, \nIN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com BEGIN:VALARM ACTION:display DESCRIPTION:Stretching session in Auditorium in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Off The Record (OTR) session: "Experiences and challenges in worki ng with Druid." DTSTART:20170728T095500Z DTEND:20170728T104000Z DTSTAMP:20260414T144605Z UID:session/WXTWfGqR5mF9qat7faA5cT@hasgeek.com SEQUENCE:0 CREATED:20170720T065305Z DESCRIPTION:\n LAST-MODIFIED:20170722T165522Z LOCATION:Room 1 - MLR Convention Centre\, Whitefield\nBengaluru\, \nIN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com BEGIN:VALARM ACTION:display DESCRIPTION:Off The Record (OTR) session: "Experiences and challenges in w orking with Druid." in Room 1 in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Off The Record (OTR) session: "ML and data engineering in fleet ma nagement and logistics." DTSTART:20170728T095500Z DTEND:20170728T105500Z DTSTAMP:20260414T144605Z UID:session/UruGhk3tJc8C53Kg3kSLZR@hasgeek.com SEQUENCE:0 CREATED:20170712T082301Z DESCRIPTION:\n LAST-MODIFIED:20170722T165817Z LOCATION:Auditorium - MLR Convention Centre\, Whitefield\nBengaluru\, \nIN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com BEGIN:VALARM ACTION:display DESCRIPTION:Off The Record (OTR) session: "ML and data engineering in flee t management and logistics." in Auditorium in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Evening beverage break (banquet hall) DTSTART:20170728T103500Z DTEND:20170728T110500Z DTSTAMP:20260414T144605Z UID:session/47kicy11SrG7GEe2Y8LeYc@hasgeek.com SEQUENCE:0 CREATED:20170519T054122Z DESCRIPTION:\n LAST-MODIFIED:20170722T162822Z LOCATION:Banquet hall - MLR Convention Centre\, Whitefield\nBengaluru\, \n IN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com BEGIN:VALARM ACTION:display DESCRIPTION:Evening beverage break (banquet hall) in Banquet hall in 5 min utes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Off The Record (OTR) session: "Learning data science." DTSTART:20170728T105500Z DTEND:20170728T115500Z DTSTAMP:20260414T144605Z UID:session/B16ucb3aoGui4tbbZwARk2@hasgeek.com SEQUENCE:0 CREATED:20170722T151018Z DESCRIPTION:\n LAST-MODIFIED:20170722T165838Z LOCATION:Banquet hall - MLR Convention Centre\, Whitefield\nBengaluru\, \n IN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com BEGIN:VALARM ACTION:display DESCRIPTION:Off The Record (OTR) session: "Learning data science." in Banq uet hall in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Evening beverage break (auditorium) DTSTART:20170728T105500Z DTEND:20170728T113500Z DTSTAMP:20260414T144605Z UID:session/Hxz3V25MGh3XvKurYzn91g@hasgeek.com SEQUENCE:0 CREATED:20170519T054938Z DESCRIPTION:\n LAST-MODIFIED:20170722T162738Z LOCATION:Auditorium - MLR Convention Centre\, Whitefield\nBengaluru\, \nIN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com BEGIN:VALARM ACTION:display DESCRIPTION:Evening beverage break (auditorium) in Auditorium in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Augmenting Solr’s NLP capabilities with Deep Learning features t o match images. DTSTART:20170728T113500Z DTEND:20170728T115500Z DTSTAMP:20260414T144605Z UID:session/Pqcf3KSrKPdM1owcrwYz1P@hasgeek.com SEQUENCE:2 CATEGORIES:Crisp talk for data engineering track,Intermediate CREATED:20170718T130213Z DESCRIPTION:1) Searching similar and exact images using deep learning (Imp ortance and problems associated)\n2) Solr – a popular text search engine \n3) Augmenting Solr with Deep learning features\n4) Self-taught hashing\n 5) Performance metrics\n6) Demo\n\n### Speaker bio\n\nI work as a data eng ineer at DataWeave\, a company that provides Competitive Intelligence as a Service for retailers and consumer brands. Here\, I helped develop deep l earning and machine-learning infrastructure for large scale product matchi ng capabilities. \n \nI am a keen enthusiast of open source projects\, and have been closely associated with a project that integrated TensorFlow wi th DeepDetect. \n\nI was among the top-5 finalists in the Xerox Research Innovation Challenge - 2016\, and winner of the Jaipur Hackathon -2015. On e of my projects - sign language converter (SLC) - was among the semi-fina l entries at TI Innovation Challenge India Design Contest 2015. \n\nI have also co-authored publications that have been accepted in Applied Intellig ence\, Knowledge Based System\, and International Conference of Machine-Le arning and Cybernetics.\n LAST-MODIFIED:20230810T072606Z LOCATION:Auditorium - MLR Convention Centre\, Whitefield\nBengaluru\, \nIN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com URL:https://hasgeek.com/fifthelephant/2017/schedule/augmenting-solrs-nlp-c apabilities-with-deep-learning-features-to-match-images-Pqcf3KSrKPdM1owcrw Yz1P BEGIN:VALARM ACTION:display DESCRIPTION:Augmenting Solr’s NLP capabilities with Deep Learning featur es to match images. in Auditorium in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Near real-time indexing/search in e-commerce marketplace: approach es and learnings. DTSTART:20170728T115500Z DTEND:20170728T124000Z DTSTAMP:20260414T144605Z UID:session/CnbzAhxFzAK2u8jYhhLhfs@hasgeek.com SEQUENCE:2 CATEGORIES:Full talk for data engineering track,Intermediate CREATED:20170718T130635Z DESCRIPTION:Outline \n1. Introduction to Solr/Lucene ecosystem [ For every one]\n2. Search & E-commerce search use case [ For Everyone ]\n3. Mar ketPlace Search\n4. Approaches to Marketplace search\n5. Case for N ear Real Time Search : Customer Experience [ For everyone ]\n6. Tech nical Challenges in Near real time search : [ Intermediate ]\n7. So lr Cloud for NRT : What works & What doesn't [ Intermediate ]\n8. Alternate Approaches to NRT : (DocValues\, Parallel Indexes\, Lucene Code cs) [Advanced]\n9. Building a RealTime search from First Princip les [Intermediate/Advanced]\n10. Monitoring/Benchmarking [Advanc ed]\n11. Other Solutions\n\n### Speaker bio\n\nUmesh Prasad is a solr/lucene contributor. He is currently a Senior Search Architect Consul tant with Lucidworks and part of the Advisory team.\n He has a decade of experience building search engine\, middleware and learning system for ne w/different usecases and different scales. Before Lucidworks \, he was par t of Search & Data platform @ Flipkart for 5 years\, where he came up with this alternative solution for providing consistent customer experience du ring BBD traffic.\n He first fell in love with Lucene and Search in 2007 while building Vertical search engine for Verse Innovation (company behin d dailyhunt now) and chose to dig his heels deeper. He also a brief stint with Payments@Amazon. Personally Umesh is customer obsessed and a custome r experience champion. His dream is to leverage technology and cloud to t ransform education and healthcare in rural India. He finished his B.Tech f rom IIT Kanpur in 2006.\n LAST-MODIFIED:20230810T072606Z LOCATION:Auditorium - MLR Convention Centre\, Whitefield\nBengaluru\, \nIN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com URL:https://hasgeek.com/fifthelephant/2017/schedule/near-real-time-indexin g-search-in-e-commerce-marketplace-approaches-and-learnings-CnbzAhxFzAK2u8 jYhhLhfs BEGIN:VALARM ACTION:display DESCRIPTION:Near real-time indexing/search in e-commerce marketplace: appr oaches and learnings. in Auditorium in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Feedback and closing DTSTART:20170728T115500Z DTEND:20170728T121000Z DTSTAMP:20260414T144605Z UID:session/4z8QarCo7Ayq5SxYc92dSf@hasgeek.com SEQUENCE:0 CREATED:20170712T095630Z DESCRIPTION:\n LAST-MODIFIED:20170722T163021Z LOCATION:Banquet hall - MLR Convention Centre\, Whitefield\nBengaluru\, \n IN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com BEGIN:VALARM ACTION:display DESCRIPTION:Feedback and closing in Banquet hall in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Flash talks – presentations by the audience DTSTART:20170728T121000Z DTEND:20170728T125500Z DTSTAMP:20260414T144605Z UID:session/RA3xVDLMpvrrBQf2gf1yRr@hasgeek.com SEQUENCE:0 CREATED:20170519T054139Z DESCRIPTION:\n LAST-MODIFIED:20170722T163024Z LOCATION:Banquet hall - MLR Convention Centre\, Whitefield\nBengaluru\, \n IN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com BEGIN:VALARM ACTION:display DESCRIPTION:Flash talks – presentations by the audience in Banquet hall in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT BEGIN:VEVENT SUMMARY:Feedback and closing DTSTART:20170728T124000Z DTEND:20170728T125500Z DTSTAMP:20260414T144605Z UID:session/Cz6xRfQevYRzm3D7JK7doD@hasgeek.com SEQUENCE:0 CREATED:20170519T055157Z DESCRIPTION:\n LAST-MODIFIED:20170722T162746Z LOCATION:Auditorium - MLR Convention Centre\, Whitefield\nBengaluru\, \nIN ORGANIZER;CN="The Fifth Elephant":MAILTO:no-reply@hasgeek.com BEGIN:VALARM ACTION:display DESCRIPTION:Feedback and closing in Auditorium in 5 minutes TRIGGER:-PT5M END:VALARM END:VEVENT END:VCALENDAR