About the Course

DataHack Summit 2019 was a grand success as it broke all previous records. The conference saw over 1200 attendees, 30+ hack sessions, 70+ talks, 8 workshops and a whole lot more learning and fun!

The conference featured top thought leaders in Artificial Intelligence and Machine Learning, and the top Data Scientists and Machine Learning Engineers from across the globe. A wide variety of topics were covered. Here’s a word cloud illustrating this:

These videos are of all three days of the conference and are exclusively available only to the conference attendees until our next conference in 2020.

Course curriculum

  • 1
    Day 1- 13 November 2019
    • Opening Remarks- Kunal Jain
    • Auditorium 1- KeyNote-Data Science Is Not about How Many Models You Build! by Eric Weber
    • Auditorium 1- Hack Session-Video Encoding & Classification using Deep Learning by Axel De Romblay
    • Auditorium 1 - Power Session- Role of Latent Variables in Machine Learning by Dr. Sarabjot Singh
    • Auditorium 1 - Power Session - Borderless AI - A Healthcare Perspective by Tarry Singh
    • Auditorium 1 - Power Session - Efficient 8-Bit Quantization of Transformer Neural Machine Language Translation Model by Nishant Agrawal
    • Auditorium 1 - Panel Discussion - Why do 85% of AI Projects Fail?
    • Auditorium 1 - Hack Session - State of Transfer Learning in NLP: BERT vs GPT2 vs XLNet by Sudalai Raj Kumar (SRK)
    • Auditorium 2- Power Session - Why is Enterprise Problem-Solving Not Like Chess or Go or ImageNet or Kaggle challenges? by Dr. Vikas Agrawal
    • Auditorium 2- Hack Session - Applying Deep Transfer Learning for NLP by Dipanjan Sarkar
    • Auditorium 2- Power Session - Evolution of Deep Learning: A biological perspective by Dr. Jie Mei
    • Auditorium 2- Hack Session - Intent Identification for Indic languages by Krupal Modi
    • Auditorium 2- Power Session - Identifying the Operational and Transitional States of a Machine by Anurag Sahay
    • Auditorium 2- Hack Session - Graph Convolutional Networks for Semi-Supervised Classification by Samiran Roy
    • Auditorium 2- Power Session - Quantum Machine Learning in the NISQ Era by Dr. Mandaar Pande
    • Auditorium 3- Power Session - The Current State and Limitations of Natural Language Processing (NLP) by Mathangi Sri
    • Auditorium 3- Hack Session - High performance data science using Swift by Mohd Sanad
    • Auditorium 3- Power Session - Personalisation is not just about Recommendation Engines, it's Much More! by Ujjyaini Mitra
    • Auditorium 3- Hack Session- Federated Learning using Deep Learning by Bargava Subramaniam & Tuhin Sharma
    • Auditorium 3- Power Session - Can the Complex HR Analytics Space Benefit by using ML models? by Kavita Dwivedi
    • Auditorium 3- Power Session - Tackling Real World Optimization Problems using AI by Varun Khandelwal
    • Auditorium 3- Hack Session - All you need to know about Deploying DL models using Tensorflow Serving by Tata Ganesh
  • 2
    Day 2- 14 November 2019
    • Auditorium 1 - Power Session - Industrial Deep Learning: Formulations & Success Stories by Vijay Gabale
    • Auditorium 1- KeyNote - Using Technology to Save Lives by Dr. Geetha Manjunath
    • Auditorium 1- Power Session - Framework to Manage End to End ML Projects by Kiran R
    • Auditorium 1- Power Session - AI/ML based Transformation in the Telecom Industry by Dr. Sunil Kumar Vuppala
    • Auditorium 1- Power Session - Finding shortest route for a cab ride using Reinforcement Learning by Dr. Sayan Ranu
    • Auditorium 1- Power Session - Deep Learning for Aesthetics: Training a Machine to See What’s Beautiful by Dat Tran
    • Auditorium 1- Panel Discussion - Is fooling an AI really that easy?
    • Auditorium 1- Power Session - Performing Machine Learning in Few KBs of RAM by Prateek Jain
    • Auditorium 1- Power Session - Reinforcement learning in the real world: Industrial applications perspective by Dr. Harshad Khadilkar
    • Auditorium 2- Hack Session - Haptic Learning: Inferring Anatomical Features using Deep Networks by Akshay Bahadur
    • Auditorium 2- Hack Session - Evaluating ML Models for Bias – Build an Interpretable Model using a Financial Dataset by Rajesh Jeyapaul & Prateek Goyal
    • Auditorium 2- Hack Session - Creating and Deploying a Pocket Yoga Trainer using Deep Learning by Mohsin Hasan & Apurva Gupta
    • Auditorium 2- Power Session - A Closer Look at Essential Data Sources in FinTech by Ratnakar Pandey & Wasimakram Binnal
    • Auditorium 2- Power Session - Overview of Game Intelligence and Informatics by Tridib Mukherjee
    • Auditorium 2- Power Session - Analyzing Streaming Data using Online Learning by Dr. Sayan Putatunda
    • Auditorium 2- Power Session - Challenges in Application of Commonsense Knowledge, in NLP and AI solutions by Madhav Kaushik
    • Auditorium 2- Hack Session - Demystifying BERT: How to Interpret NLP Models? by Logesh Kumar
    • Auditorium 3- Hack Session - Hyperparameter optimization using Bayesian Optimization by Abhishek Periwal
    • Auditorium 3- Hack Session - Handling High Velocity Data Streams using Kafka & Spark by Durga Gadiraju
    • Auditorium 3- Hack Session - Automated Portfolio Management using Reinforcement Learning by Sonam Srivastava
    • Auditorium 3- Hack Session - Image Captioning using Attention Models by Rajesh Bhat & Souradip Chakraborty
    • Auditorium 3- Power Session - Why Do we need to Solve our Problems Geospatially? by Rishabh Jain
    • Auditorium 3- Hack Session - Building an End-to-End Credit Risk Model by Arihant Jain
  • 3
    Day 3 - 15 November 2019
    • Auditorium 1- Hack Session - Deploy DL models in production using PyTorch by Vishnu Subramaniam
    • Auditorium 1- KeyNote - Top Hacks from a Kaggle Grandmaster by Pavel Pleskov
    • Auditorium 1- Hack Session - Image ATM (Automatic Tagging Machine) - Image Classification for Everyone by Dat Tran
    • Auditorium 1- Hack Session - Morphing images using Deep Generative Models (GANs) by Xander Steenbrugge
    • Auditorium 1- Panel Discussion - What Sets the Top Hackers Apart?
    • Auditorium 1- Hack Session - Deep Learning for Search in E-Commerce by Sonu Sharma & Atul Agarwal
    • Auditorium 1- Hack Session - Generating Synthetic Images from Textual Description using GANs by Shibsankar Das
    • Auditorium 1- Closing Remarks by Kunal Jain
    • Auditorium 2- Hack Session - Using Genetic Algorithms to build Machine Learning Pipelines by Sahil Verma
    • Auditorium 2- Hack Session - RL in Real Life: Implementation Guide by Hardik Meisheri & Richa Verma
    • Auditorium 2- Hack Session - Enabling Intelligent Search using Question-Answer Models by Abhishek Jha, Priya Shree & Atul Singh (Ph.D.)
    • Auditorium 2- Hack Session - Deep Learning in Graph based Recommender Systems by Janu Verma
    • Auditorium 2- Hack Session - Data Engineering in Action: Working with Data at scale by Rishabh Raj & Amit Prabhu
    • Auditorium 3- Hack Session - Feature Engineering for Image Data by Aishwarya Singh & Pulkit Sharma
    • Auditorium 3- Hack Session - Graph based Feature Engineering - Sourabh Jha
    • Auditorium 3- Hack Session - Synthetic Handwritten Text Data Generation using Recurrent Neural Networks(RNN) by Raghav Bali
    • Auditorium 3- Hack Session - MLOps - Putting ML Models to Production by Akash Tandon
    • Auditorium 3- Hack Session - Content Based Recommender System using Transfer Learning by Sitaram Tadepalli
    • Auditorium 3- Hack Session - Exploring PyTorch for AI Assistance in Medical Imaging by Abhishek Kumar
    • Auditorium 3- Hack Session - Multi Time Series Seq2Seq LSTM Model in PyTorch by Ankur Verma