Master reinforcement learning a popular area of machine learning starting with the basics:
discover how agents and the environment evolve and then gain a clear picture of how they are
inter-related. You'll then work with theories related to reinforcement learning and see the
concepts that build up the reinforcement learning process. Reinforcement Learning discusses
algorithm implementations important for reinforcement learning including Markov's Decision
process and Semi Markov Decision process. The next section shows you how to get started with
Open AI before looking at Open AI Gym. You'll then learn about Swarm Intelligence with Python
in terms of reinforcement learning. The last part of the book starts with the TensorFlow
environment and gives an outline of how reinforcement learning can be applied to TensorFlow.
There's also coverage of Keras a framework that can be used with reinforcement learning.
Finally you'll delve into Google's Deep Mind and see scenarios where reinforcement learning
can be used. What You'll Learn Absorb the core concepts of the reinforcement learning process
Use advanced topics of deep learning and AI Work with Open AI Gym Open AI and Python Harness
reinforcement learning with TensorFlow and Keras using Python Who This Book Is ForData
scientists machine learning and deep learning professionals developers who want to adapt and
learn reinforcement learning.
