Machine Learning Beginner Reinforcement Learning in Python Udemy coupons

Machine Learning: Beginner Reinforcement Learning in Python

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

Created by Milo Spencer-Harper | 1.5 hours on-demand video course

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.

What you’ll learn

  • Machine Learning
  • Artificial Intelligence
  • Neural Networks
  • Reinforcement Learning
  • Deep Q Learning
  • OpenAI Gym
  • Keras
  • Tensorflow
  • Bellman Equation

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