November 10 2020

Machine Learning: Beginner Reinforcement Learning in Python

Machine Learning: Beginner Reinforcement Learning in Python
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
Bellman Equation

Basic knowledge of Python

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.

Who this course is for
Anyone interested in machine learning


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