Practical Deep Reinforcement Learning with Python

Introducing Practical Smart Agents Development using Python, PyTorch, and TensorFlow KEY FEATURES ● Exposure to well-known RL techniques, including Monte-Carlo, Deep Q-Learning, Policy Gradient, and Actor-Critical. ● Hands-on experience with TensorFlow and PyTorch on Reinforcement Learning projects. ● Everything is concise, up-to-date, and visually explained with simplified mathematics. DESCRIPTION Reinforcement learning is a fascinating branch of AI that differs from standard machine learning in several ways. Adaptation and learning in an unpredictable environment is the part of this project. There are numerous real-world applications for reinforcement learning these days, including medical, gambling, human imitation activity, and robotics. This book introduces readers to reinforcement learning from a pragmatic point of view. The book does involve mathematics, but it does not attempt to overburden the reader, who is a beginner in the field of reinforcement learning. The book brings a