Artificial Intelligence IV - Reinforcement Learning in Java
4.7
Udemy1,842 learners
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This course is perfect for those interested in Artificial Intelligence and Reinforcement Learning. It covers the mathematical background of Reinforcement Learning, such as Markov Decision Processes, value-iteration, policy-iteration and Q-learning. It also covers pathfinding algorithms with Q-learning and Q-learning with neural networks. This course is a great way to learn the state-of-the-art approach to Reinforcement Learning and gain a better understanding of Artificial Intelligence.
Machine Learning: Beginner Reinforcement Learning in Python
4.6
Udemy497 learners
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This course is perfect for beginners to machine learning. In this course, you will learn to code a neural network in Python capable of delayed gratification. You will be introduced to the concept of reinforcement learning, and use the NChain game provided by the Open AI institute to understand how the computer can get a small reward if it goes backwards, but a much larger reward if it learns to make short term sacrifices by persistently pressing forwards. You will also learn Deep Q Learning - a revolutionary technique invented by Google DeepMind to teach neural networks to play chess, Go and Atari. Join this course to explore the exciting advances in artificial intelligence and learn to code a neural network in Python.
Advanced Reinforcement Learning in Python: from DQN to SAC
4.2
Udemy1,234 learners
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This Advanced Reinforcement Learning course on Udemy is the most comprehensive of its kind. It will teach you to implement powerful Deep Reinforcement Learning algorithms in Python using PyTorch and PyTorch lightning. You will learn to create adaptive Artificial Intelligence agents that can solve decision-making tasks, combining Reinforcement Learning techniques with Neural Networks and Deep Learning methods. This course will also prepare you for the next courses in the series, where you will explore other advanced methods. With practical modules and jupyter notebooks, you will be able to develop your skills from scratch. Don't miss this opportunity to become an expert in Reinforcement Learning!
Advanced Reinforcement Learning in Python: cutting-edge DQNs
4.8
Udemy891 learners
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This Advanced Reinforcement Learning course on Udemy is the most comprehensive of its kind. It will teach you to implement powerful Deep Reinforcement Learning algorithms in Python using PyTorch and PyTorch lightning. You will learn to create adaptive Artificial Intelligence agents that can solve decision-making tasks, combining Reinforcement Learning techniques with Neural Networks and Deep Learning methods. This course will also prepare you for the next courses in the series, where you will explore other advanced methods. With practical skills in mind, you will implement algorithms from scratch in jupyter notebooks. Don't miss out on this opportunity to learn the state of the art in Reinforcement Learning!
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