A hands-on guide enriched with examples to master deep
reinforcement learning algorithms with Python Key Features Your
entry point into the world of artificial intelligence using the
power of Python An example-rich guide to master various RL and DRL
algorithms Explore various state-of-the-art architectures along
with math Book DescriptionReinforcement Learning (RL) is the
trending and most promising branch of artificial intelligence.
Hands-On Reinforcement learning with Python will help you master
not only the basic reinforcement learning algorithms but also the
advanced deep reinforcement learning algorithms. The book starts
with an introduction to Reinforcement Learning followed by OpenAI
Gym, and TensorFlow. You will then explore various RL algorithms
and concepts, such as Markov Decision Process, Monte Carlo methods,
and dynamic programming, including value and policy iteration. This
example-rich guide will introduce you to deep reinforcement
learning algorithms, such as Dueling DQN, DRQN, A3C, PPO, and TRPO.
You will also learn about imagination-augmented agents, learning
from human preference, DQfD, HER, and many more of the recent
advancements in reinforcement learning. By the end of the book, you
will have all the knowledge and experience needed to implement
reinforcement learning and deep reinforcement learning in your
projects, and you will be all set to enter the world of artificial
intelligence. What you will learn Understand the basics of
reinforcement learning methods, algorithms, and elements Train an
agent to walk using OpenAI Gym and Tensorflow Understand the Markov
Decision Process, Bellman's optimality, and TD learning Solve
multi-armed-bandit problems using various algorithms Master deep
learning algorithms, such as RNN, LSTM, and CNN with applications
Build intelligent agents using the DRQN algorithm to play the Doom
game Teach agents to play the Lunar Lander game using DDPG Train an
agent to win a car racing game using dueling DQN Who this book is
forIf you're a machine learning developer or deep learning
enthusiast interested in artificial intelligence and want to learn
about reinforcement learning from scratch, this book is for you.
Some knowledge of linear algebra, calculus, and the Python
programming language will help you understand the concepts covered
in this book.
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