Theme and format
The Fifth Elephant 2017 is a four-track conference on:
- Data engineering – building pipelines and platforms; exposure to latest open source tools for data mining and real-time analytics.
- Application of Machine Learning (ML) in diverse domains such as IOT, payments, e-commerce, education, ecology, government, agriculture, computational biology, social network analysis and emerging markets.
- Hands-on tutorials on data mining tools, and ML platforms and techniques.
- Off-the-record (OTR) sessions on privacy issues concerning data; building data pipelines; failure stories in ML; interesting problems to solve with data science; and other relevant topics.
The Fifth Elephant is a conference for practitioners, by practitioners.
Talk submissions are now closed.
You must submit the following details along with your proposal, or within 10 days of submission:
- Draft slides, mind map or a textual description detailing the structure and content of your talk.
- Link to a self-record, two-minute preview video, where you explain what your talk is about, and the key takeaways for participants. This preview video helps conference editors understand the lucidity of your thoughts and how invested you are in presenting insights beyond your use case. Please note that the preview video should be submitted irrespective of whether you have spoken at past editions of The Fifth Elephant.
- If you submit a workshop proposal, you must specify the target audience for your workshop; duration; number of participants you can accommodate; pre-requisites for the workshop; link to GitHub repositories and documents showing the full workshop plan.
About the conference
This year is the sixth edition of The Fifth Elephant. The conference is a renowned gathering of data scientists, programmers, analysts, researchers, and technologists working in the areas of data mining, analytics, machine learning and deep learning from different domains.
We invite proposals for the following sessions, with a clear focus on the big picture and insights that participants can apply in their work:
- Full-length, 40-minute talks.
- Crisp, 15-minute talks.
- Sponsored sessions, of 15 minutes and 40 minutes duration (limited slots available; subject to editorial scrutiny and approval).
- Hands-on tutorials and workshop sessions of 3-hour and 6-hour duration where participants follow instructors on their laptops.
- Off-the-record (OTR) sessions of 60-90 minutes duration.
- Proposals will be filtered and shortlisted by an Editorial Panel.
- Proposers, editors and community members must respond to comments as openly as possible so that the selection processs is transparent.
- Proposers are also encouraged to vote and comment on other proposals submitted here.
We will notify you if we move your proposal to the next round or reject it. A speaker is NOT confirmed for a slot unless we explicitly mention so in an email or over any other medium of communication.
Selected speakers must participate in one or two rounds of rehearsals before the conference. This is mandatory and helps you to prepare well for the conference.
There is only one speaker per session. Entry is free for selected speakers.
Partial or full grants, covering travel and accomodation are made available to speakers delivering full sessions (40 minutes) and workshops. Grants are limited, and are given in the order of preference to students, women, persons of non-binary genders, and speakers from Asia and Africa.
Commitment to Open Source
We believe in open source as the binding force of our community. If you are describing a codebase for developers to work with, we’d like for it to be available under a permissive open source licence. If your software is commercially licensed or available under a combination of commercial and restrictive open source licences (such as the various forms of the GPL), you should consider picking up a sponsorship. We recognise that there are valid reasons for commercial licensing, but ask that you support the conference in return for giving you an audience. Your session will be marked on the schedule as a “sponsored session”.
- Deadline for submitting proposals: June 10
- First draft of the coference schedule: June 20
- Tutorial and workshop announcements: June 20
- Final conference schedule: July 5
- Conference dates: 27-28 July
For more information about speaking proposals, tickets and sponsorships, contact email@example.com or call +91-7676332020.
How we are building serverless architectures for Deep Learning & NLP at Episource
Serverless is the new kid on the block, and an exciting one at that ! As Anand Chitipothu puts it, it’s rapidly becoming the Uber of cloud computing resources.
At Episource, we have been working on creating a scalable NLP pipeline for scalable information extraction from medical discharge summaries. However, processing millions of charts can be expensive too. In this talk, we will show how we created a serverless and event driven architecture for deep learning. The platform requires no manual intervention and minimal upkeep & maintenance. We will share the challenges in creating such an architecture, especially when requirements of immutable configuration and heavy data workloads don’t go away easily. A detailed demo of the architecture would be showcased as well.
The audience can expect to learn a lot from our experiences and maybe go serverless at their roles as well !
- Problems & Challenges
- Why Serverless ?
- Components of this serverless NLP architecture
- Towards an immutable configuration
- Architecture Diagram & Details
- Impact of the serverless architecture
The slides link has been shared, and will be updated regularly.
I am currently leading the NLP & Data Science practice at Episource, a US healthcare company. My daily work revolves around working on semantic technologies and computational linguistics (NLP), building algorithms and machine learning models, researching data science journals and architecting secure product backends in the cloud.
Techstack that my team and I typically work on includes;
Testing Frameworks: unittest, pytest
Automation & Configuration Management: Ansible, Docker, Vagrant
CI: Travis CI
Cloud Services: AWS, Google Cloud, MS Azure
APIs: Bottle, CherryPy, Flask
Databases: MySQL, SQLite, MSSQL, RDF stores, Neo4J, ElasticSearch, MongoDB, Redis
Editor: Sublime, Pycharm
I have architected multiple commercial NLP solutions in the area of healthcare, foods & beverages, finance and retail. I am deeply involved in functionally architecting large scale business process automation & 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 multiple forums like Data Science Central, LinkedIn and my blog NLP Wave.
I love teaching and mentoring students. I speak regularly on NLP and text analytics at conferences and meetups like Pycon India and PyData. I have also taught multiple hands-on session at IIM Lucknow and MDI Gurgaon. I have mentored students from schools like ISB Hyderabad, BITS Pilani, Madras School of Economics. When bored - I like to fall back on Asimov to lead me into an alternate reality.
- LinkedIn : https://in.linkedin.com/in/manasranjankar
- Contribution to Gensim (PR #625): https://github.com/RaRe-Technologies/gensim/blob/develop/gensim/scripts/glove2word2vec.py
- Blog: http://unlocktext.com/
- Related Blog Article: http://unlocktext.com/index.php/2015/12/14/using-glove-vectors-in-gensim/
- Context oriented NLP: https://www.linkedin.com/pulse/context-extraction-better-sentiment-analysis-manas-ranjan-kar?trk=prof-post
- Analysing product reviews for context cues: http://www.datasciencecentral.com/profiles/blogs/impactful-text-analytics-for-smarter-businesses