[ DevCourseWeb.com ] Machine Learning: Beginner Reinforcement Learning in Python



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MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch

Genre: eLearning | Language: English + .srt | Duration: 24 lectures (1h 44m) | Size: 611.5 MB

How to teach a neural network to play a game using delayed gratification in 146 lines of Python code

What you'll learn:

Machine Learning

Artificial Intelligence

Neural Networks

Reinforcement Learning

Deep Q Learning

OpenAI Gym

Keras

Tensorflow

Bellman Equation



Requirements

Basic knowledge of Python



Description

This course is designed for beginners to machine learning. Some of the most exciting advances in artificial intelligence have occurred by challenging neural networks to play games. I will introduce the concept of reinforcement learning, by teaching you to code a neural network in Python capable of delayed gratification.



We will use the NChain game provided by the Open AI institute. The computer gets a small reward if it goes backwards, but if it learns to make short term sacrifices by persistently pressing forwards it can earn a much larger reward. Using this example I will teach you Deep Q Learning - a revolutionary technique invented by Google DeepMind to teach neural networks to play chess, Go and Atari.



Use Winrar to Extract. And use a shorter path when extracting, such as C: drive



ALSO ANOTHER TIP: You Can Easily Navigate Using Winrar and Rename the Too Long File/ Folder Name if Needed While You Cannot in Default Windows Explorer. You are Welcome ! :)



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