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Python Reinforcement Learning Projects - Eight hands-on projects exploring reinforcement learning algorithms using TensorFlow (Paperback)
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Python Reinforcement Learning Projects - Eight hands-on projects exploring reinforcement learning algorithms using TensorFlow (Paperback)
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Implement state-of-the-art deep reinforcement learning algorithms
using Python and its powerful libraries Key Features Implement
Q-learning and Markov models with Python and OpenAI Explore the
power of TensorFlow to build self-learning models Eight AI projects
to gain confidence in building self-trained applications Book
DescriptionReinforcement learning is one of the most exciting and
rapidly growing fields in machine learning. This is due to the many
novel algorithms developed and incredible results published in
recent years. In this book, you will learn about the core concepts
of RL including Q-learning, policy gradients, Monte Carlo
processes, and several deep reinforcement learning algorithms. As
you make your way through the book, you'll work on projects with
datasets of various modalities including image, text, and video.
You will gain experience in several domains, including gaming,
image processing, and physical simulations. You'll explore
technologies such as TensorFlow and OpenAI Gym to implement deep
learning reinforcement learning algorithms that also predict stock
prices, generate natural language, and even build other neural
networks. By the end of this book, you will have hands-on
experience with eight reinforcement learning projects, each
addressing different topics and/or algorithms. We hope these
practical exercises will provide you with better intuition and
insight about the field of reinforcement learning and how to apply
its algorithms to various problems in real life. What you will
learn Train and evaluate neural networks built using TensorFlow for
RL Use RL algorithms in Python and TensorFlow to solve CartPole
balancing Create deep reinforcement learning algorithms to play
Atari games Deploy RL algorithms using OpenAI Universe Develop an
agent to chat with humans Implement basic actor-critic algorithms
for continuous control Apply advanced deep RL algorithms to games
such as Minecraft Autogenerate an image classifier using RL Who
this book is forPython Reinforcement Learning Projects is for data
analysts, data scientists, and machine learning professionals, who
have working knowledge of machine learning techniques and are
looking to build better performing, automated, and optimized deep
learning models. Individuals who want to work on self-learning
model projects will also find this book useful.
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