Reinforcement Learning: Qwik Start
Like many other areas of machine learning research, reinforcement learning (RL) is evolving at breakneck speed. Just as they have done in other research areas, researchers are leveraging deep learning to achieve state-of-the-art results.
In particular, reinforcement learning has significantly outperformed prior ML techniques in game playing, reaching human-level and even world-best performance on Atari, beating the human Go champion, and is showing promising results in more difficult games like Starcraft II.
In this lab, you will learn the basics of reinforcement learning by building a simple game, which has been modelled off of a sample provided by OpenAI Gym.
In this lab, you will:
- Understand the fundamental concepts of reinforcement learning.
- Create an AI Platform Tensorflow 2.1 Notebook.
- Clone the sample repository from the training data analyst repo found on Github.
- Read, understand, and run the steps found in the notebook.
Once you're ready, scroll down and follow the steps below to get your lab environment set up.
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Create an AI Platform Notebook
Clone the sample code