8:00 AM |
Coffee & Registration
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9:00 AM |
Opening Notes
Conference Committee - James + Manoj
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9:15 AM |
Keynote: Siraj Raval [Maths Behind Deep Learning]
Siraj Raval
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10:00 AM |
Regression Analysis - The good, the bad and the untold
Jalem Raj Rohit
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Things to know while choosing a Deep Learning library
Saurabh Agarwal
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Machine Learning as a Service
Anand Chitipothu
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10:30 AM |
Topic Modelling with Gensim
Parul Sethi
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Proximal Policy Optimization : The new kid in the RL Jungle
Shubham Gupta
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11:00 AM |
Building camera based intelligent applications
Nabarun Pal
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Difficulties in working with the government data and how can tech help us resolve it.
Ankita Mathur
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11:30 AM |
Using RNNs to implement a Full Adder using PyTorch
Madhur Tandon
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Deriving insights in minutes from serverless IoT Data Pipeline
Narendran R
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12:00 PM |
Keynote: Ponnurangam Kumaraguru [Data Science for Social Good]
Ponnurangam Kumaraguru
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12:45 PM |
Lunch
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1:45 PM |
Lightning Talks
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2:30 PM |
Machine Learning Architectures
Shagun Sodhani
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Information Diffusion in a Twitter Network
Sagar Chand Agarwal
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Deep Reinforcement Learning: A hands-on approach
Shubham Dokania
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3:00 PM |
Interestingness of interestingness measures
Simrat Hanspal
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Dimensionality Reduction Techniques - "You can compress!"
Manan Singh, Nilay Shrivastava
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3:30 PM |
Transfer Learning Using Tensorflow and Keras
Amita Kapoor
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Computer Vision in self driving cars
Ridhwan Luthra
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4:00 PM |
Hitchhiker's guide to using Neo4J: Trials & Tribulations of deploying a scalable graph API on Cloud
Vinay Kumar
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Convex.jl: A native Julia package for real or complex domain Convex Optimization
Ayush Pandey
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4:30 PM |
Evening Tea & Snacks
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4:45 PM |
Keynote: Farhat Habib [Machine Learning in Online Advertising]
Farhat Habib
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5:30 PM |
Wrapping Day 1
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5:45 PM |
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