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[Crowdcast] Reinforcement Q-Learning from Scratch in Python with OpenAI Gym


February 16, 2021 10:00 am EET

 🌟 Overview

Most of you have probably heard of AI learning to play computer games on their own, a very popular example being Deepmind. Deepmind hit the news when their AlphaGo program defeated the South Korean Go world champion in 2016. There had been many successful attempts in the past to develop agents with the intent of playing Atari games like Breakout, Pong, and Space Invaders.

Each of these programs follow a paradigm of Machine Learning known as Reinforcement Learning. If you’ve never been exposed to reinforcement learning before, the following is a very straightforward analogy for how it works.

🎓 What will you learn?
When you have completed this workshop, you will understand how to:
🔥What Reinforcement Learning is and how it works
🔥How to work with OpenAI Gym
🔥How to implement Q-Learning in Python

👩‍💻 Who should attend?
All technology enthusiasts are welcome to attend the webinar!

👩‍🏫 Prerequisites
☁ Register for a free IBM Cloud Account:
prior to the event to get the most out of our workshop.

🎙️ Speaker
Tal Neeman, IBM Developer Advocate