27-28 July 2017, Bangalore
Status: Accepting submissions

Theme and format

The Fifth Elephant 2017 is a four-track conference on:

  1. Data engineering – building pipelines and platforms; exposure to latest open source tools for data mining and real-time analytics.
  2. 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.
  3. Hands-on tutorials on data mining tools, and ML platforms and techniques.
  4. 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.

You must submit the following details along with your proposal, or within 10 days of submission:

  1. Draft slides, mind map or a textual description detailing the structure and content of your talk.
  2. 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.
  3. 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:

Selection Process

  1. Proposals will be filtered and shortlisted by an Editorial Panel.
  2. Proposers, editors and community members must respond to comments as openly as possible so that the selection processs is transparent.
  3. Proposers are also encouraged to vote and comment on other proposals submitted here.

Selection Process Flowchart

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.

Travel grants

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”.

Important Dates:

Contact

For more information about speaking proposals, tickets and sponsorships, contact info@hasgeek.com or call +91-7676332020.

Propose a session

# Speaker Section Level +1 Submitted
1 How to make your language Machine Learning and NLP friendly with an audio documentation toolkit
Subhashish Panigrahi (@psubhashish) Full talk for Data in Government track Intermediate 1 0 Sun, 28 May
2 Governance using Apache Atlas: Why and How
vimal sharma (@svimal2106) Full talk for data engineering track Intermediate 1 0 Fri, 26 May
3 Lessons learned from building a globally distributed database service from the ground up
Dharma Shukla (@dharmashukla) Full talk for data engineering track Intermediate 8 0 Fri, 26 May
4 What explains our marks?
Anand S (@sanand0) Crisp talk for Data in Government track Beginner 4 0 Wed, 24 May
5 Do you know what's on TV?
Bharath Mohan (@bharathmohan) Full talk for data engineering track Intermediate 5 1 Mon, 22 May
6 How to read a user's mind? Designing algorithms for contextual recommendations
Bharath Mohan (@bharathmohan) Crisp talk for data engineering track Beginner 4 1 Mon, 22 May
7 IoT case study: Taking Machine Learning model to a smart phone or low cost hardware
Amit Doshi (@amitdoshi) Full talk for data engineering track Intermediate 3 1 Mon, 22 May
8 Scalability truths and serverless architectures - why it is harder with stateful, data-driven systems
Regunath Balasubramanian (@regunathb) Full talk for data engineering track Intermediate 3 1 Mon, 22 May
9 What database? - a practical guide to selection from NoSQL, SQL and Polyglot data stores
Regunath Balasubramanian (@regunathb) Full talk for data engineering track Intermediate 1 1 Mon, 22 May
10 Plumbing data science pipelines
Krishnapriya Satagopan (@kpsatagopan) Crisp talk for data engineering track Intermediate 9 0 Mon, 22 May
11 Wait, I can explain this! (ML models explaining their predictions)
Ramprakash R (@ramprakashr) Crisp talk for data engineering track Intermediate 17 1 Mon, 22 May
12 Interestingness of interestingness measures
Simrat Hanspal (@simrathanspal) Full talk for data engineering track Advanced 16 4 Sun, 30 Apr
13 Guarding OSM from invalid edits with Gabbar
Bhargav Kowshik (@bkowshik) Full talk for data engineering track Intermediate 4 4 Sun, 30 Apr
14 Learnings from building TV viewership platform for 100 Million users at zapr
Agam Jain (@agamj20) Full talk for data engineering track Intermediate 4 1 Sun, 30 Apr
15 Seamless Hadoop Deployments - Myth or Reality?
Ragesh Rajagopalan (@rajagopr) Crisp talk for data engineering track Beginner 10 3 Sun, 30 Apr
16 Adapting Bandit Algorithms to optimise user experience at Practo Consult
Santosh GSK (@santoshgadde) Crisp talk for data engineering track Intermediate 26 4 Sun, 30 Apr
17 Designing Cost Effective Cloud Native Applications
Tarun Gupta (@tarung) Crisp talk for data engineering track Intermediate 3 1 Sun, 30 Apr
18 Processing mission critical events in real time
Tarun Gupta (@tarung) Crisp talk for data engineering track Intermediate 5 3 Sun, 30 Apr
19 How we are building serverless architectures for Deep Learning & NLP at Episource
Manas Ranjan Kar (@manasrkar-episource) Full talk for data engineering track Intermediate 5 2 Sun, 30 Apr
20 Human Centric API Design
Gagan Gupta (@gagangupt16) Crisp talk for data engineering track Beginner 6 1 Sun, 30 Apr
21 Transforming India's Budgets into Open Linked Data
Gaurav Godhwani (@gggodhwani) Full talk for Data in Government track Intermediate 6 2 Sun, 30 Apr
22 Questions and Intuition for Tackling Deep Learning Problems
Govind Chandrasekhar (@gc20) Full talk for data engineering track Intermediate 2 2 Sat, 29 Apr
23 Out of Stone age : Why investing in developer tools is necessary for big data development to scale.
Shankar Manian (@shanm) Full talk for data engineering track Intermediate 11 1 Sat, 29 Apr
24 Beyond unit tests: Deployment and testing for Hadoop/Spark workflows
Anant Nag (@nntnag17) Full talk for data engineering track Intermediate 10 1 Fri, 28 Apr
25 Making data scientists life easy with Docker
Abhishek Kumar (@meabhishekkumar) Full talk for data engineering track Intermediate 12 3 Fri, 28 Apr
26 Real-time Monitoring of Big Data Workflows
Akshay Rai (@akshayrai) Full talk for data engineering track Intermediate 12 3 Fri, 28 Apr
27 Causal Analytics in Retail and Telco
Gaurav Goswami (@gauravgoswami) Crisp talk for data engineering track Intermediate 1 5 Fri, 28 Apr
28 Designing Machine Learning Pipelines for Mining Transactional SMS Messages
Paul Meinshausen (@pmeins) Full talk for data engineering track Intermediate 11 2 Fri, 28 Apr
29 Data Processing Engine with Lambda Architecture at WalmartLabs
Shaik Asifullah (@shaikasif) Crisp talk for data engineering track Intermediate 11 2 Thu, 27 Apr
30 Dr. Elephant: Achieving Quicker, Easier, and Cost-effective Big Data Analytics
Akshay Rai (@akshayrai) Full talk for data engineering track Intermediate 11 2 Thu, 27 Apr
31 Fraud Detection & Risk Management in Payment Systems implemented using a Hybrid Memory Database
Srini V. Srinivasan (@drvsrinivasan) Full talk in Payment Analytics track Intermediate 20 0 Thu, 27 Apr
32 Using data pipelines to navigate your data ocean
Vipul Mathur (@vipulmathur) Full talk for data engineering track Beginner 15 2 Thu, 27 Apr
33 The Python ecosystem for data science - Landscape Overview
Ananth Krishnamoorthy (@akrishnamoorthy) Full talk for data engineering track Beginner 5 3 Thu, 27 Apr
34 A Recommender for Match-making: Item-based CF, PageRank, Evaluation techniques & Deep-Learning
prabhakar srinivasan (@prabhacar7) Full talk for data engineering track Advanced 4 1 Thu, 27 Apr
35 Search Infrastructure @ Slack using Lambda Architecture
Ananth Durai (@vananth22) Full talk for data engineering track Intermediate 7 1 Thu, 27 Apr
36 Can Security Data Science defend against next "WannaCry"?
Satnam Singh, PhD (@satnam-datageek) Full talk for data engineering track Beginner 0 0 Wed, 26 Apr
37 Suuchi - Toolkit to build distributed systems
Sriram R (@brewkode) Full talk for data engineering track Intermediate 24 4 Wed, 26 Apr
38 Discovery tools for Government data analytics
Venkateswaran M (@venkateswaranm) Crisp talk for Data in Government track Intermediate 6 3 Tue, 25 Apr
39 Machine Learning from Practice to Production
Ramanan Balakrishnan (@ramananbalakrishnan) Full talk for data engineering track Beginner 6 0 Tue, 25 Apr
40 Streaming video analytics using deep learning on large scale surveillance data @ Fractal Analytics
abhineet verma (@averma) Full talk for data engineering track Advanced 17 2 Tue, 25 Apr
41 Autonomous Grid using Machine Learning
Charan Puvvala (@charanpuvvala) Full talk for data engineering track Intermediate 4 1 Tue, 25 Apr
42 Optimising Model performance using automated ML pipeline for predicting purchase propensity @ Fractal Analytics
PadmaCh (@padmach) Full talk for data engineering track Advanced 20 4 Tue, 25 Apr
43 Application of machine learning in oil and gas industry
Priyanka Raghavan (@priyankaraghavan) Crisp talk for data engineering track Beginner 13 3 Tue, 25 Apr
44 Application of AI in e-commerce industry from product search to customer satisfaction
Dr Amit Garg (@garg78) Crisp talk for data engineering track Intermediate 25 4 Sat, 22 Apr
45 Learning representations of text for NLP
Anuj Gupta (@anujgupta82) Workshops Intermediate 27 1 Wed, 19 Apr
46 Google Spanner: Beginning of the End of the NoSQL World?
Vijay Srinivas Agneeswaran, Ph.D (@vijayagneeswaran) Full talk for data engineering track Intermediate 7 2 Tue, 18 Apr
47 Big Data Computations: Comparing Apache HAWQ, Druid, Google Spanner and GPU Databases
Vijay Srinivas Agneeswaran, Ph.D (@vijayagneeswaran) Full talk for data engineering track Intermediate 6 3 Tue, 18 Apr
48 Maths for machine learning without tears
Harshad Saykhedkar (@harshss) Workshops Intermediate 3 1 Mon, 17 Apr
49 Working with Apache Spark in Eta
Jyothsna Srinivas (@jyothsnasrinivas) Full talk for data engineering track Intermediate 17 1 Sun, 16 Apr
50 AI in the Education Sector
Agnes Shanthi Mohan (@agnesshanthimohan) Crisp talk for data engineering track Intermediate 14 1 Sat, 15 Apr
51 Get the AI Advantage in E-commerce
Vinita Mohan (@vinitamohanofficial) Crisp talk for data engineering track Intermediate 17 1 Fri, 14 Apr
52 ML For Personalization At Scale @ Nearbuy
ankit kohli (@ankitko) Full talk for data engineering track Advanced 21 2 Wed, 12 Apr
53 Credit where Credit is due: Using data science to lend to customers without a credit history
Vanitha DSilva (@vanithadsilva) Crisp talk for data engineering track Intermediate 14 4 Tue, 11 Apr
54 micro-ATMs: The what, the why and the how
Vanitha DSilva (@vanithadsilva) Full talk in Payment Analytics track Intermediate 15 4 Tue, 11 Apr
55 Machine Learning Applications in Cisco Spark Collaboration SaaS
Narayanan Subramaniam (@narayanan-subramaniam) Crisp talk for data engineering track Intermediate 1 2 Sat, 8 Apr
56 How to engineer a personalization system that can handle Paytm scale
Harinder Takhar (@harindertakhar) (proposing) Full talk for data engineering track Advanced 8 2 Tue, 4 Apr
57 From a recommendations carousel to personalizing entire app - personalization story at paytm
Harinder Takhar (@harindertakhar) (proposing) Crisp talk for data engineering track Advanced 7 1 Tue, 4 Apr
58 How Paytm uses k8s for global expansion
Harinder Takhar (@harindertakhar) (proposing) Full talk for data engineering track Intermediate 4 6 Tue, 4 Apr
59 Large scale business stats aggregation using Kafka
Vinothkumar Raman (@vinothkumarraman) Full talk of 40 mins duration Intermediate 20 2 Thu, 30 Mar
60 Blockchain for business and government
Mani Madhukar (@manimadhukar) Crisp talk for Data in Government track Beginner 4 5 Mon, 20 Mar
61 Streaming for life, universe and everything using Confluent Platform
Aastha Rai (@aastha0304) Crisp talk for data engineering track Intermediate 6 3 Tue, 14 Mar