Submissions

The Fifth Elephant 2017

On data engineering and application of ML in diverse domains

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All submissions

How Paytm uses k8s for global expansion

Pranshu Saxena (@pranshus)

  • 7 comments
  • Rejected
  • Tue, 04 Apr
Section: Full talk for data engineering track Technical level: Intermediate

Large scale business stats aggregation using Kafka

Vinothkumar Raman (@vinothkumarraman)

  • 2 comments
  • Rejected
  • Thu, 30 Mar
Technical level: Intermediate

ML For Personalization At Scale @ Nearbuy

ankit kohli (@ankitko)

  • 4 comments
  • Rejected
  • Wed, 12 Apr
Section: Full talk for data engineering track Technical level: Advanced

Machine Learning Applications in Cisco Spark Collaboration SaaS

Narayanan Subramaniam (@narayanan-subramaniam)

  • 2 comments
  • Rejected
  • Sat, 08 Apr
Section: Crisp talk for data engineering track Technical level: Intermediate

micro-ATMs: The what, the why and the how

Vanitha DSilva (@vanithadsilva)

  • 5 comments
  • Rejected
  • Tue, 11 Apr
Section: Full talk in Payment Analytics track Technical level: Intermediate

From a recommendations carousel to personalizing entire app - personalization story at paytm

Charumitra Pujari (@charupujari)

  • 2 comments
  • Confirmed & scheduled
  • Tue, 04 Apr
Section: Full talk in Payment Analytics track Technical level: Advanced

Blockchain for business and government

Mani Madhukar (@manimadhukar)

  • 5 comments
  • Rejected
  • Mon, 20 Mar
Section: Crisp talk for Data in Government track Technical level: Beginner

How to engineer a personalization system that can handle Paytm scale

Harinder Takhar (@harindertakhar) (proposing)

  • 2 comments
  • Rejected
  • Tue, 04 Apr
Section: Full talk for data engineering track Technical level: Advanced

Distributed Consensus and Data Safety: NewSQL Perspective

Vijay Srinivas Agneeswaran, Ph.D (@vijayagneeswaran)

  • 5 comments
  • Confirmed & scheduled
  • Tue, 18 Apr
Section: Full talk for data engineering track Technical level: Intermediate

Credit where Credit is due: Using data science to lend to customers without a credit history

Vanitha DSilva (@vanithadsilva)

  • 4 comments
  • Waitlisted
  • Tue, 11 Apr
Section: Crisp talk for data engineering track Technical level: Intermediate

Big Data Computations: Comparing Apache HAWQ, Druid, Google Spanner and GPU Databases

Vijay Srinivas Agneeswaran, Ph.D (@vijayagneeswaran)

  • 9 comments
  • Rejected
  • Tue, 18 Apr
Section: Full talk for data engineering track Technical level: Intermediate

Learning representations of text for NLP

Anuj Gupta (@anujgupta82)

  • 5 comments
  • Rejected
  • Wed, 19 Apr
Section: Workshops Technical level: Intermediate

Working with Apache Spark in Eta

Jyothsna Srinivas (@jyothsnasrinivas)

  • 3 comments
  • Cancelled
  • Sun, 16 Apr
Section: Full talk for data engineering track Technical level: Intermediate

5 Lessons I’ve Learned Tackling Product Matching for E-commerce

Govind Chandrasekhar (@gc20)

  • 3 comments
  • Confirmed & scheduled
  • Sat, 29 Apr
Section: Full talk for data engineering track Technical level: Intermediate

The Python ecosystem for data science - Landscape Overview

Ananth Krishnamoorthy (@akrishnamoorthy)

  • 4 comments
  • Rejected
  • Thu, 27 Apr
Section: Full talk for data engineering track Technical level: Beginner

Human Centric API Design

Gagan Gupta (@gagangupt16)

  • 1 comments
  • Rejected
  • Sun, 30 Apr
Section: Crisp talk for data engineering track Technical level: Beginner

Designing Machine Learning Pipelines for Mining Transactional SMS Messages

Paul Meinshausen (@pmeins)

  • 2 comments
  • Confirmed & scheduled
  • Fri, 28 Apr
Section: Full talk for data engineering track Technical level: Intermediate

Machine Learning from Practice to Production

Ramanan Balakrishnan (@ramananbalakrishnan)

  • 2 comments
  • Confirmed & scheduled
  • Tue, 25 Apr
Section: Full talk for data engineering track Technical level: Beginner

Designing Cost Effective Cloud Native Applications

Tarun Gupta (@tarung)

  • 1 comments
  • Rejected
  • Sun, 30 Apr
Section: Crisp talk for data engineering track Technical level: Intermediate

Using data pipelines to navigate your data ocean

Vipul Mathur (@vipulmathur)

  • 2 comments
  • Rejected
  • Thu, 27 Apr
Section: Full talk for data engineering track Technical level: Beginner

Out of Stone age : Why investing in developer tools is necessary for big data development to scale.

Shankar Manian (@shanm)

  • 1 comments
  • Rejected
  • Sat, 29 Apr
Section: Full talk for data engineering track Technical level: Intermediate

Dr. Elephant: Achieving Quicker, Easier, and Cost-effective Big Data Analytics

Akshay Rai (@akshayrai)

  • 2 comments
  • Rejected
  • Thu, 27 Apr
Section: Crisp talk for Data in Government track Technical level: Intermediate

Adapting Bandit Algorithms to optimise user experience at Practo Consult

Santosh GSK (@santoshgadde)

  • 4 comments
  • Confirmed & scheduled
  • Sun, 30 Apr
Section: Crisp talk for data engineering track Technical level: Intermediate

Discovery tools for Government data analytics

Venkateswaran M (@venkateswaranm)

  • 8 comments
  • Rejected
  • Tue, 25 Apr
Section: Crisp talk for Data in Government track Technical level: Intermediate

Gabbar: Machine learning to guard OpenStreetMap

Bhargav Kowshik (@bkowshik)

  • 5 comments
  • Confirmed & scheduled
  • Sun, 30 Apr
Section: Full talk for data engineering track Technical level: Intermediate

Suuchi - Toolkit to build distributed systems

Sriram R (@brewkode)

  • 9 comments
  • Confirmed & scheduled
  • Wed, 26 Apr
Section: Full talk for data engineering track Technical level: Intermediate

Transforming India's Budgets into Open Linked Data

Gaurav Godhwani (@gggodhwani)

  • 4 comments
  • Confirmed & scheduled
  • Sun, 30 Apr
Section: Full talk for Data in Government track Technical level: Intermediate

Search Infrastructure @ Slack using Lambda Architecture

Ananth Durai (@vananth22)

  • 5 comments
  • Cancelled
  • Thu, 27 Apr
Section: Full talk for data engineering track Technical level: Intermediate

Application of AI in e-commerce industry from product search to customer satisfaction

Dr Amit Garg (@garg78)

  • 5 comments
  • Rejected
  • Sat, 22 Apr
Section: Crisp talk for data engineering track Technical level: Intermediate

Causal Analytics in Retail and Telco

Gaurav Goswami (@gauravgoswami)

  • 10 comments
  • Rejected
  • Fri, 28 Apr
Section: Crisp talk for data engineering track Technical level: Intermediate

Making data scientists life easy with Docker

Abhishek Kumar (@meabhishekkumar)

  • 5 comments
  • Rejected
  • Fri, 28 Apr
Section: Full talk for data engineering track Technical level: Intermediate

Autonomous Grid using Machine Learning

Charan Puvvala (@charanpuvvala)

  • 2 comments
  • Rejected
  • Tue, 25 Apr
Section: Full talk for data engineering track Technical level: Intermediate

Beyond unit tests: Deployment and testing for Hadoop/Spark workflows

Anant Nag (@nntnag17)

  • 5 comments
  • Rejected
  • Fri, 28 Apr
Section: Full talk for data engineering track Technical level: Intermediate

Processing mission critical events in real time

Tarun Gupta (@tarung)

  • 3 comments
  • Rejected
  • Sun, 30 Apr
Section: Crisp talk for data engineering track Technical level: Intermediate

A Recommender for Match-making: Item-based CF, PageRank, Evaluation techniques & Deep-Learning

prabhakar srinivasan (@prabhacar7)

  • 9 comments
  • Rejected
  • Thu, 27 Apr
Section: Full talk for data engineering track Technical level: Advanced

Real-time Monitoring of Big Data Workflows

Akshay Rai (@akshayrai)

  • 4 comments
  • Rejected
  • Fri, 28 Apr
Section: Full talk for data engineering track Technical level: Intermediate

Application of machine learning in oil and gas industry

Priyanka Raghavan (@priyankaraghavan)

  • 3 comments
  • Rejected
  • Tue, 25 Apr
Section: Crisp talk for data engineering track Technical level: Beginner

Seamless Hadoop Deployments - Myth or Reality?

Ragesh Rajagopalan (@rajagopr)

  • 3 comments
  • Rejected
  • Sun, 30 Apr
Section: Crisp talk for data engineering track Technical level: Beginner

How we are building serverless architectures for Deep Learning & NLP at Episource

Manas Ranjan Kar (@manasrkar-episource)

  • 4 comments
  • Confirmed & scheduled
  • Sun, 30 Apr
Section: Crisp talk for data engineering track Technical level: Intermediate

Fraud Detection & Risk Management in Payment Systems implemented using a Hybrid Memory Database

Srini V. Srinivasan (@drvsrinivasan)

  • 0 comments
  • Confirmed & scheduled
  • Thu, 27 Apr
Section: Full talk in Payment Analytics track Technical level: Intermediate

Optimising Model performance using automated ML pipeline for predicting purchase propensity @ Fractal Analytics

PadmaCh (@padmach)

  • 6 comments
  • Rejected
  • Tue, 25 Apr
Section: Full talk for data engineering track Technical level: Advanced

What database? - a practical guide to selection from NoSQL, SQL and Polyglot data stores

Regunath Balasubramanian (@regunathb)

  • 2 comments
  • Confirmed & scheduled
  • Mon, 22 May
Section: Full talk for data engineering track Technical level: Intermediate

Wait, I can explain this! (ML models explaining their predictions)

Ramprakash R (@ramprakashr)

  • 4 comments
  • Confirmed & scheduled
  • Mon, 22 May
Section: Crisp talk for data engineering track Technical level: Intermediate

Plumbing data science pipelines

Krishnapriya Satagopan (@kpsatagopan)

  • 3 comments
  • Confirmed & scheduled
  • Mon, 22 May
Section: Crisp talk for data engineering track Technical level: Intermediate

Interestingness of interestingness measures

Simrat Hanspal (@simrathanspal)

  • 7 comments
  • Under evaluation
  • Sun, 30 Apr
Section: Full talk for data engineering track Technical level: Advanced

Scalability truths and serverless architectures - why it is harder with stateful, data-driven systems

Regunath Balasubramanian (@regunathb)

  • 5 comments
  • Rejected
  • Mon, 22 May
Section: Full talk for data engineering track Technical level: Intermediate

Learnings from building TV viewership platform for 100 Million users at zapr

Agam Jain (@agamjain)

  • 3 comments
  • Rejected
  • Sun, 30 Apr
Section: Full talk for data engineering track Technical level: Intermediate

Developing and Deploying Analytics for Internet of Things (IoT)

Amit Doshi (@amitdoshi)

  • 7 comments
  • Confirmed & scheduled
  • Mon, 22 May
Section: Sponsored session Technical level: Intermediate

Do you know what's on TV?

Bharath Mohan (@bharathmohan)

  • 10 comments
  • Confirmed & scheduled
  • Mon, 22 May
Section: Full talk for data engineering track Technical level: Intermediate

How to prepare your language for Machine Learning and NLP with an open audio documentation toolkit

Subhashish Panigrahi (@psubhashish)

  • 0 comments
  • Rejected
  • Sun, 28 May
Section: Full talk for Data in Government track Technical level: Intermediate

What explains our marks?

Anand S (@sanand0)

  • 3 comments
  • Confirmed & scheduled
  • Wed, 24 May
Section: Crisp talk for Data in Government track Technical level: Beginner

How to read a user's mind? Designing algorithms for contextual recommendations

Bharath Mohan (@bharathmohan)

  • 1 comments
  • Rejected
  • Mon, 22 May
Section: Crisp talk for data engineering track Technical level: Beginner

Saving taxes without breaking laws using Machine Learning

GS Jayendran (@vyakyajay)

  • 1 comments
  • Rejected
  • Thu, 01 Jun
Section: Full talk in Payment Analytics track Technical level: Beginner

Apache Atlas Introduction: Need for Governance and Metadata management

Vimal Sharma (@svimal2106)

  • 4 comments
  • Confirmed & scheduled
  • Fri, 26 May
Section: Full talk for data engineering track Technical level: Intermediate

Reality of Data Modelling: Many analysts, one dataset: Multiple Results

Lakshman Prasad (@becomingguru)

  • 0 comments
  • Rejected
  • Wed, 31 May
Section: Full talk for data engineering track Technical level: Intermediate

Lessons learned from building a globally distributed database service from the ground up

Dharma Shukla (@dharmashukla)

  • 9 comments
  • Confirmed & scheduled
  • Fri, 26 May
Section: Full talk for data engineering track Technical level: Intermediate

Open data in government: challenges, and the case of Telangana Open Data Initiative

Rakesh Dubbudu (@rakeshdubbudu)

  • 0 comments
  • Confirmed & scheduled
  • Wed, 12 Jul
Section: Full talk for Data in Government track Technical level: Beginner

Augmenting Solr’s NLP Capabilities with Deep-Learning Features to Match Images

Kumar Shubham (@kumar-shubham)

  • 2 comments
  • Confirmed & scheduled
  • Fri, 09 Jun
Section: Crisp talk for data engineering track Technical level: Intermediate

Talk Less, Chat More

Ashutosh (@ashutrv)

  • 4 comments
  • Rejected
  • Fri, 02 Jun
Section: Full talk for data engineering track Technical level: Beginner

Unlock sub-second SQL analytics over terrabytes of data with Hive and Druid

Nishant Bangarwa (@nishantbangarwa)

  • 2 comments
  • Rejected
  • Wed, 07 Jun
Section: Full talk for data engineering track Technical level: Beginner

Unless you measure it; you can’t improve it - Data pipelines for your business KPIs and KRAs

Ketan Khairnar (@ketankhairnar)

  • 6 comments
  • Rejected
  • Thu, 08 Jun
Section: Workshops Technical level: Intermediate

Lessons Learnt building and optimizing a self service Data Platform on Apache Spark at Indix

Matild Reema (@matild-reema)

  • 3 comments
  • Rejected
  • Fri, 09 Jun
Section: Full talk for data engineering track Technical level: Intermediate

Using Probabilistic Data Structures to Build Real-Time Monitoring Dashboards

Rahul Ramesh (@rahul-ramesh-17)

  • 0 comments
  • Rejected
  • Fri, 09 Jun
Section: Crisp talk for data engineering track Technical level: Beginner

Distributed Machine Learning - Challenges and Oppurtunities

Anand Chitipothu (@anandology)

  • 0 comments
  • Confirmed & scheduled
  • Sat, 10 Jun
Section: Crisp talk for data engineering track Technical level: Intermediate

Interactive Realtime Dashboards on Data Streams using Kafka, Druid and Superset

Nishant Bangarwa (@nishantbangarwa)

  • 1 comments
  • Confirmed & scheduled
  • Wed, 07 Jun
Section: Full talk for data engineering track Technical level: Intermediate

Leonardo Machine Learning Foundation - Adding Intelligence to your Enterprise Business

sainath v (@sapcloudengineers)

  • 0 comments
  • Rejected
  • Fri, 09 Jun
Section: Crisp talk for data engineering track Technical level: Beginner

ML Goes Fruitful

Preeti Negi (@preeti14dec)

  • 2 comments
  • Rejected
  • Sat, 10 Jun
Section: Workshops Technical level: Beginner

Democratising Data in the Microservices World

Rajaram Mallya (@rajarammallya)

  • 1 comments
  • Rejected
  • Sat, 10 Jun
Section: Full talk for data engineering track Technical level: Intermediate

Machine Learning as a Service

Bargava Subramanian (@barsubra)

  • 1 comments
  • Confirmed
  • Tue, 30 May
Section: Workshops Technical level: Beginner

How Machine Learning Algorithms evolved at Haptik while it's Chatbot catered to 200 million messages

krupal Modi (@superkrups)

  • 2 comments
  • Rejected
  • Fri, 09 Jun
Section: Full talk for data engineering track Technical level: Intermediate

Data in drug discovery

Shefali Lathwal (@shefalilathwal)

  • 2 comments
  • Rejected
  • Fri, 09 Jun
Section: Full talk for data engineering track Technical level: Beginner

Gen Z BI Paradigm - A Scalable , hybrid and collaborative Visualization Architecture using Spark , No SQL and Restful API

Deepikavalli A (@deepikavalli)

  • 2 comments
  • Rejected
  • Sat, 10 Jun
Section: Crisp talk for data engineering track Technical level: Intermediate

Multi-channel conversational chatbot platform powered by NLP engine

Prakash Mall (@prakashmall)

  • 1 comments
  • Rejected
  • Sat, 10 Jun
Section: Crisp talk for data engineering track Technical level: Beginner

Making sense of Digital and Physical Documents using ML and Optical Character Recognition

Nitin Saraswat (@chunky)

  • 0 comments
  • Rejected
  • Sat, 10 Jun
Section: Full talk for data engineering track Technical level: Intermediate

How to build scalable and robust data pipeline iteratively.

Danish M (@pixelgenie)

  • 2 comments
  • Rejected
  • Sun, 04 Jun
Section: Full talk for data engineering track Technical level: Intermediate

Application Dependency Data Performance Mapping tool - Dynatrace

Chandrish M (@chandrish)

  • 0 comments
  • Rejected
  • Fri, 09 Jun
Section: Crisp talk for data engineering track Technical level: Beginner

Near Real time indexing/search in E-commerce marketplace : Approaches and Learnings

Umesh Prasad (@umeshprasad)

  • 1 comments
  • Confirmed & scheduled
  • Fri, 09 Jun
Section: Full talk for data engineering track Technical level: Intermediate

Building camera based intelligent applications

Nabarun Pal (@palnabarun)

  • 0 comments
  • Rejected
  • Sat, 10 Jun
Section: Crisp talk for data engineering track Technical level: Intermediate

Recommendation Engine for Wide Transactions

Harjindersingh Mistry (@harjinder-hari)

  • 0 comments
  • Rejected
  • Fri, 09 Jun
Section: Full talk for data engineering track Technical level: Beginner

Zero down time ML model swap using docker and kubernetes

anugrah nayar (@codewalker)

  • 0 comments
  • Awaiting details
  • Sat, 10 Jun
Section: Full talk for data engineering track Technical level: Beginner

Maps ❤️ Data: A voyage across the world of geo-visualization

Rasagy Sharma (@rasagy)

  • 0 comments
  • Confirmed & scheduled
  • Sat, 10 Jun
Section: Full talk for data engineering track Technical level: Intermediate

Bits and joules: data-driven energy systems

Deva P. Seetharam (@dpseetharam)

  • 0 comments
  • Confirmed & scheduled
  • Tue, 25 Jul
Section: Full talk for Data in Government track Technical level: Beginner

Building a converged platform for data analytics

David Sangma (@davidsangma) (proposing)

  • 2 comments
  • Rejected
  • Mon, 12 Jun
Section: Crisp talk for data engineering track Technical level: Advanced

How We Built Our Machine Intelligence To Help Humans Save Lives

Zainul Charbiwala (@zainulcharbiwala)

  • 0 comments
  • Confirmed & scheduled
  • Sat, 22 Jul
Section: Full talk for Data in Government track Technical level: Beginner

Interactive Data Visualisation using Markdown

Amit Kapoor (@amitkaps)

  • 0 comments
  • Confirmed & scheduled
  • Mon, 12 Jun
Section: Full talk for data engineering track Technical level: Beginner

Streaming for life, universe and everything using Confluent Platform

Aastha Rai (@aastha0304)

  • 4 comments
  • Rejected
  • Tue, 14 Mar
Section: Crisp talk for data engineering track Technical level: Intermediate

Building a Generic but highly customizable and scalable Anomaly Detection System @ Badoo

Akash Mishra (@sleepythread)

  • 3 comments
  • Rejected
  • Wed, 31 May
Section: Full talk for data engineering track Technical level: Intermediate

Modeling intent of the user using Probabilistic Machine Learning

Sarah Masud (@sara-02)

  • 3 comments
  • Cancelled
  • Wed, 07 Jun
Section: Full talk for data engineering track Technical level: Intermediate