Reinforcement learning overview (Reinforcement learning with TensorFlow Agents) скачать в хорошем качестве

Reinforcement learning overview (Reinforcement learning with TensorFlow Agents)

Wei Wei, a Developer Advocate for TensorFlow, kicks off a new series on reinforcement learning where we explore how you can leverage TensorFlow Agents to build your own reinforcement learning agents. Wei explains how reinforcement learning can be used to train agents to make the best decisions when performing actions in environments to maximize rewards. Resources: Reinforcement Learning Lecture Series 2021 (DeepMind x UCL) → https://goo.gle/3B6td3x Introduction to Reinforcement Learning → https://goo.gle/3rwDWAV Chip Design with Deep Reinforcement Learning → https://goo.gle/3uC9veH Quickly Training Game-Playing Agents with Machine Learning → https://goo.gle/3gsCx8v Leveraging Machine Learning for Game Development → https://goo.gle/3rAt7OB OpenAI Gym → https://goo.gle/3srq5Ly Github → https://goo.gle/3B6OPfW Chapters: 00:00 Series introduction 00:55 Reinforcement learning example 01:30 What is reinforcement learning 02:24 Supervised learning vs. reinforcement learning 03:44 Taxonomy 05:13 Reinforcement learning applications 06:34 Training environments 08:13 References and summary Watch more Reinforcement learning with TensorFlow Agents episodes → https://goo.gle/reinforcement-learning Subscribe to TensorFlow → https://goo.gle/TensorFlow Ask your questions on the TF Forum → https://goo.gle/discuss_tensorflow #TensorFlow #MachineLearning #ML product: TensorFlow - General; fullname: Wei Wei;