Description:

Reinforcement Learning algorithms becoming more and more sophisticated every day which is evident from the recent win of AlphaGo and AlphaGo Zero (https://deepmind.com/blog/alphago-zero-learning-scratch/ ). OpenAI has provided toolkit openai gym for research and development of Reinforcement Learning algorithms.

In this workshop, we will focus on introduction to the basic concepts and algorithms in Reinforcement Learning and hands on coding.

<H3> Content </H3>

• Introduction to Reinforcement Learning (~ 15 mins)
• Introduction to Reinforcement Learning algorithms (~ 15 mins)
• Setting up OpenAI Gym and other dependencies
• Implementing simple algorithm using one of the atari games from OpenAI Gym (~ 1 Hr 15 mins)
• Quick overview of deep reinforcement learning and important papers in the area (~ 15 mins)

Prerequisites:

Participants must be well versed with python. Some exposure to analytics libraries in python such as numpy, pandas, keras, tensorflow, pytorch would help.

Content URLs:

Content will be shared on github after the workshop. I will share detailed plan for the workshop in a while for the review.

Speaker Info:

My name is Saurabh Deshpande. I am working as a Senior Software engineer at SAS Research and Development centre, Pune. I have been using python since last three years and also teaching python in my company. I have more then 11 years of experience in architecture and development of enterprise scale web applications, cloud technologies such as AWS, OpenStack, CloudFoundry, server less and microservice based architectures. Since past three years I have been exploring and experimenting in the field of visual analytics, machine learning, deep learning using python based libraries such as pandas, scikit learn, pytorch and tensorflow.

Speaker Links:

https://www.linkedin.com/in/saurabh1deshpande/