Home | Amazing | Today | Tags | Publishers | Years | Account | Search 
Keras Reinforcement Learning Projects: 9 projects exploring popular reinforcement learning techniques to build self-learning agents

Buy

A practical guide to mastering reinforcement learning algorithms using Keras

Key Features

  • Build projects across robotics, gaming, and finance fields, putting reinforcement learning (RL) into action
  • Get to grips with Keras and practice on real-world unstructured datasets
  • Uncover advanced deep learning algorithms such as Monte Carlo, Markov Decision, and Q-learning

Book Description

Reinforcement learning has evolved a lot in the last couple of years and proven to be a successful technique in building smart and intelligent AI networks. Keras Reinforcement Learning Projects installs human-level performance into your applications using algorithms and techniques of reinforcement learning, coupled with Keras, a faster experimental library.

The book begins with getting you up and running with the concepts of reinforcement learning using Keras. You'll learn how to simulate a random walk using Markov chains and select the best portfolio using dynamic programming (DP) and Python. You'll also explore projects such as forecasting stock prices using Monte Carlo methods, delivering vehicle routing application using Temporal Distance (TD) learning algorithms, and balancing a Rotating Mechanical System using Markov decision processes.

Once you've understood the basics, you'll move on to Modeling of a Segway, running a robot control system using deep reinforcement learning, and building a handwritten digit recognition model in Python using an image dataset. Finally, you'll excel in playing the board game Go with the help of Q-Learning and reinforcement learning algorithms.

By the end of this book, you'll not only have developed hands-on training on concepts, algorithms, and techniques of reinforcement learning but also be all set to explore the world of AI.

What you will learn

  • Practice the Markov decision process in prediction and betting evaluations
  • Implement Monte Carlo methods to forecast environment behaviors
  • Explore TD learning algorithms to manage warehouse operations
  • Construct a Deep Q-Network using Python and Keras to control robot movements
  • Apply reinforcement concepts to build a handwritten digit recognition model using an image dataset
  • Address a game theory problem using Q-Learning and OpenAI Gym

Who this book is for

Keras Reinforcement Learning Projects is for you if you are data scientist, machine learning developer, or AI engineer who wants to understand the fundamentals of reinforcement learning by developing practical projects. Sound knowledge of machine learning and basic familiarity with Keras is useful to get the most out of this book

Table of Contents

  1. Overview of Keras Reinforcement Learning
  2. Simulating random walks
  3. Optimal Portfolio Selection
  4. Forecasting stock market prices
  5. Delivery Vehicle Routing Application
  6. Prediction and Betting Evaluations of coin flips using Markov decision processes
  7. Build an optimized vending machine using Dynamic Programming
  8. Robot control system using Deep Reinforcement Learning
  9. Handwritten Digit Recognizer
  10. Playing the board game Go
  11. What is next?
(HTML tags aren't allowed.)

Visual Basic 2005 Jumpstart
Visual Basic 2005 Jumpstart
Visual Basic 2005 Jumpstart is written for VB 6 programmers who have yet to move to Visual Basic 2005, the latest release of Microsoft Visual Basic, one of the world's most popular programming languages. With VB 2005, Microsoft has given VB 6 developers a host of reasons to upgrade now, including the return of VB 6 features omitted from earlier...
The Executive's Guide to Information Technology
The Executive's Guide to Information Technology
What Every Senior Manager and Consultant Should Know About Managing Effective IT Departments

"This book sheds light on one of the most challenging topics for corporate officers –how to create and manage a high-performance IT department and obtain higher returns from technology-invested capital. The techniques and tools provided show...

Extreme Innovation: Using the Information Evolution Model to Grow Your Business
Extreme Innovation: Using the Information Evolution Model to Grow Your Business
Provides a strategic model to identify, evaluate, and improve information usage patternsIn a business climate that punishes the inefficient and the slow moving, enterprises must manage their information assets more effectively than ever. Information Revolution introduces and explains the Information Evolution Model (IEM), a patent-pending framework...

Mastering Data Warehouse Design: Relational and Dimensional Techniques
Mastering Data Warehouse Design: Relational and Dimensional Techniques
At last, a balanced approach to data warehousing that leverages the techniques pioneered by Ralph Kimball and Bill Inmon

Since its groundbreaking inception, the approach to understanding data warehousing has been split into two mindsets: Ralph Kimball, who pioneered the use of dimensional modeling techniques for building the data warehouse, and...

Computer Algebra and Symbolic Computation: Mathematical Methods
Computer Algebra and Symbolic Computation: Mathematical Methods
Computer algebra is the field of mathematics and computer science that is concerned with the development, implementation, and application of algorithms that manipulate and analyze mathematical expressions. This book and the companion text, Computer Algebra and Symbolic Computation: Mathematical Methods, are an introduction to the subject that...
XML Schema Essentials
XML Schema Essentials
The definitive how-to guide that will get you quickly up to speed on the practical application of XML Schema!

Replacing XML DTDs (Document Type Definitions) as the way in which XML documents are described and validated, XML Schema allows you to describe the structure of information in an XML document and is essential for ensuring
...
©2019 LearnIT (support@pdfchm.net) - Privacy Policy