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 Автор: VnRuEn |  Дата: 10 ноября 2020|  Просмотров: 0
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В разделе: - [Информация] |
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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. Who this course is for Anyone interested in machine learning Homepage Screenshots  Welcome to |
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Machine Learning: Beginner Reinforcement Learning in Python 