Schedule

The Fifth Elephant 2016

India's most renowned data science conference

Auditorium 1

Auditorium 2

Auditorium 3

Room 1

Hall

C5 (Seminar Hall)

Training Room

08:30–09:20

Check-in and breakfast

09:20–09:30

Introduction to The Fifth Elephant 2016

09:30–10:30

Using Data to Identify the Genomic Cause of Disease

Ramesh Hariharan, Strand Life Sciences

09:35–10:20

Allocation and Forecasting in Guaranteed Delivery of Advertisements

Aditya Ramana Rachakonda, Flipkart

10:30–11:30

Keynote: The Alternative Data revolution on Wall St

Gene Ekster, Analyst and Investment Consultant

11:30–12:00

Morning tea break

12:00–12:45

ML in fin-tech - Transforming 60 crore Indian lives

Riddhi Mittal, Finomena

12:00–12:45

Purpose, Speed & Visibility : Facilitating product discovery & engagement on a e-commerce website

Ekta Grover, BloomReach Inc

12:45–13:30

Deciphering Driving Behaviour using Geospatial Temporal Data Collected from Smartphone Sensors

Aditya Karnik, Zendrive

12:45–13:30

Taking Fashion and Lifestyle Commerce Towards SKUs Using Deep Image and Text Parsing

Vijay Gabale, Infilect

13:30–14:40

Lunch

14:40–15:00

Data-Driven Decision Making in Indian Agriculture: the Present and the Future

Udit Poddar, SocialCops

14:40–15:00

RightFit- A Data Science Approach to Reduce Product Returns in Fashion e-Commerce

Ashish Kulkarni, JabongLabs

15:00–16:00

What do machine learning and high performance computing have to do with big cats in the wild?

Dr. Arjun Gopalaswamy, Indian Statistical Institute, Bangalore

15:00–15:45

Scaling the Largest Functional DataSet @Flipkart aka Catalog

Anuj Mittal, Flipkart

15:00–16:00

Birds of Feather (BoF): How much math and statistics programmers need to know to hack their way into Machine Learning?

Facilitators: Amit Kapoor, Bargava S., Ashwin Kumar

15:45–16:05

Increasing Trust and Efficiency of Data Science using dataset versioning

Venkata Pingali, Scribble Data

16:00–16:05

Birds of Feather (BoF): Alternative Data

Facilitators: Gene Ekster, Udit Poddar

16:05–16:40

Evening tea break

16:40–17:25

Hierarchical Structure, Hierarchical Bayes approach and implementation of MCMC

Soumen Dey, Indian Statistical Institute, Bangalore

16:40–17:25

Taking Analytics Applications from Labs to the Real World: Transfer Learning in Practice

Shourya Roy, Xerox Research

17:25–18:25

Djembe Jam

Auditorium 1

Auditorium 2

Auditorium 3

Room 1

Hall

C5 (Seminar Hall)

Training Room

08:30–09:20

Check-in and breakfast

09:20–09:30

Summary of day 1

10:15–11:00

Meet the needs of content marketing with the power of NLP

Balaji Vasan, Adobe Research Big Data Experience Labs

10:15–10:45

Let your Big Data Processing take flight with Apache Falcon

Pallavi Rao, InMobi

10:45–11:05

Timely Dataflow

Bharani S., ThoughtWorks

11:05–11:35

Morning tea break

11:35–12:35

Keynote: Reasoning – The Next Frontier in Data Science

Shailesh Kumar, ThirdLeap

12:35–12:55

Lessons Learned : Real-life NLP

Martin Andrews, Cambridge Business Solutions

12:35–12:55

Looking under the hood - demystifying data tools

Simrat Hanspal, Mad Street Den

12:55–14:10

Lunch

14:10–14:55

Continuous online learning for classification tasks

Saurabh Arora, Freshdesk

14:10–14:55

Scalable Realtime Analytics using Druid

Nishant Bangarwa, HortonWorks

14:55–15:40

Convolutional Neural Networks from the Other Side

Sumod Mohan, SolitonTech

14:55–15:25

Dr. Elephant - Self-Serve Performance Tuning for Hadoop and Spark

Akshay Rai, LinkedIn

15:40–16:20

Evening tea break

16:20–17:05

Model Visualisation

Amit Kapoor, NarrativeViz

16:20–16:45

Hadoop & Cloud Storage: Object Store Integration in Production

Rajesh Balamohan, HortonWorks

16:20–16:55

Birds of Feather (BoF): From Machine Learning to Deep Learning – when, how and why do you make the transition?

Facilitators: Sumod Mohan, Martin Andrews, Prasanna S, Shailesh Kumar

16:45–17:10

Machine Learning the Walmart Way with a Deep Dive into Automated Forecasting System

Anindya Sankar Dey, @WalmartLabs

17:05–17:50

Real Time Fulfilment Planning at Flipkart Scale

Jagadeesh Huliyar, Flipkart

17:10–17:30

Logging at scale using Graylog - Billion+ messages, 100K req/sec

Rohit Gupta

17:30–17:55

Reducing the world with JavaScript

Aruna S, Mapbox

17:55–18:15

Feedback and theme for 2017

Auditorium 1

Auditorium 2

Auditorium 3

Room 1

Hall

C5 (Seminar Hall)

Training Room

08:45–09:30

Check-in and Breakfast

09:30–11:00

Advanced Deep Learning Workshop – Hands-on

Martin Andrews

09:30–11:00

Introduction to Statistics and Basics of Mathematics for Data Science - the hacker's way

Bargava Subramanian

11:00–11:15

Tea Break

11:15–12:45

Contd. Advanced Deep Learning Workshop – Hands-on

11:15–12:45

Contd. Introduction to Statistics and Basics of Mathematics for Data Science - the hacker's way

12:45–13:45

Lunch

13:45–15:30

Contd. Advanced Deep Learning Workshop – Hands-on

13:45–15:30

Contd. Introduction to Statistics and Basics of Mathematics for Data Science - the hacker's way

15:30–15:45

Tea Break

15:45–17:00

Contd. Advanced Deep Learning Workshop – Hands-on

15:45–17:00

Contd. Introduction to Statistics and Basics of Mathematics for Data Science - the hacker's way

Auditorium 1

Auditorium 2

Auditorium 3

Room 1

Hall

C5 (Seminar Hall)

Training Room

08:15–09:00

Check-in and Breakfast

09:00–11:00

Deep Learning for Computer Vision

Hari C M

11:00–11:15

Tea Break

11:15–13:15

Contd. Deep Learning for Computer Vision

13:15–14:15

Lunch

14:15–16:00

Building a scalable Data Science Platform ( Luigi, Apache Spark, Pandas, Flask)

Nischal HP

16:00–16:15

Tea Break

16:15–18:00

Contd. Building a scalable Data Science Platform ( Luigi, Apache Spark, Pandas, Flask)

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