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
This course is designed for bners to machine learning.
How to teach a neural network to play a game using delayed gratification in 146 lines of Python code
Machine Learning
Artificial Intelligence
Neural Networks
Reinforcement Learning
Deep Q Learning
OpenAI Gym
Keras
Tensorflow
Bellman Equation
Basic knowledge of Python
Some of the most exciting advances in artificial intelligence have occurred by challeg 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.
Anyone interested in machine learning
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