Reinforcement Learning Training course – Entire Machine Learning Tutorial

Reinforcement learning is an space of machine learning that will involve taking suitable action to optimize reward in a distinct problem. In this whole tutorial study course, you will get a sound basis in reinforcement learning main subjects.

The program addresses Q learning, SARSA, double Q finding out, deep Q studying, and coverage gradient techniques. These algorithms are utilized in a amount of environments from the open up AI health club, including place invaders, breakout, and some others. The deep learning part takes advantage of Tensorflow and PyTorch.

The course commences with a lot more modern algorithms, this kind of as deep q finding out and coverage gradient approaches, and demonstrates the energy of reinforcement learning.

Then the training course teaches some of the elementary principles that electric power all reinforcement learning algorithms. These are illustrated by coding up some algorithms that predate deep mastering, but are nonetheless foundational to the cutting edge. These are studied in some of the far more standard environments from the OpenAI fitness center, like the cart pole challenge.

💻Code: https://github.com/philtabor/Youtube-Code-Repository/tree/grasp/ReinforcementLearning

⭐️ Study course Contents ⭐️
⌨️ (00:00:00) Intro
⌨️ (00:01:30) Intro to Deep Q Understanding
⌨️ (00:08:56) How to Code Deep Q Learning in Tensorflow
⌨️ (00:52:03) Deep Q Finding out with Pytorch Section 1: The Q Community
⌨️ (01:06:21) Deep Q Studying with Pytorch element 2: Coding the Agent
⌨️ (01:28:54) Deep Q Finding out with Pytorch component
⌨️ (01:46:39) Intro to Policy Gradients 3: Coding the key loop
⌨️ (01:55:01) How to Conquer Lunar Lander with Policy Gradients
⌨️ (02:21:32) How to Defeat Area Invaders with Coverage Gradients
⌨️ (02:34:41) How to Develop Your Have Reinforcement Learning Atmosphere Element 1
⌨️ (02:55:39) How to Produce Your Have Reinforcement Learning Setting Section 2
⌨️ (03:08:20) Fundamentals of Reinforcement Learning
⌨️ (03:17:09) Markov Choice Processes
⌨️ (03:23:02) The Examine Exploit Problem
⌨️ (03:29:19) Reinforcement Learning in the Open up AI Gym: SARSA
⌨️ (03:39:56) Reinforcement Learning in the Open up AI Health and fitness center: Double Q Mastering
⌨️ (03:54:07) Summary

Study course from Machine Learning with Phil. Check out out his YouTube channel: https://www.youtube.com/channel/UC58v9cLitc8VaCjrcKyAbrw

Discover to code for free of charge and get a developer position: https://www.freecodecamp.org

Read hundreds of content on programming: https://medium.freecodecamp.org

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