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Hands-On Artificial Intelligence with Java for Beginners

By : Joshi

1.3 (3)

Buy this Book

Hands-On Artificial Intelligence with Java for Beginners

1.3 (3)

By: Joshi

Buy this Book

Overview of this book

Artificial intelligence (AI) is increasingly in demand as well as relevant in the modern world, where everything is driven by technology and data. AI can be used for automating systems or processes to carry out complex tasks and functions in order to achieve optimal performance and productivity. Hands-On Artificial Intelligence with Java for Beginners begins by introducing you to AI concepts and algorithms. You will learn about various Java-based libraries and frameworks that can be used in implementing AI to build smart applications. In addition to this, the book teaches you how to implement easy to complex AI tasks, such as genetic programming, heuristic searches, reinforcement learning, neural networks, and segmentation, all with a practical approach. By the end of this book, you will not only have a solid grasp of AI concepts, but you'll also be able to build your own smart applications for multiple domains.

Preface

Who this book is for

What this book covers

To get the most out of this book

Get in touch

Free Chapter

Introduction to Artificial Intelligence and Java

What is machine learning?

Differences between classification and regression

Installing JDK and JRE

Setting up the NetBeans IDE

Importing Java libraries and exporting code in projects as a JAR file

Summary

Exploring Search Algorithms

An introduction to searching

Implementing Dijkstra's search

Understanding the notion of heuristics

A brief introduction to the A* algorithm

Implementing an A* algorithm

Summary

AI Games and the Rule-Based System

Introducing the min-max algorithm

Implementing an example min-max algorithm

Installing Prolog

An introduction to rule-based systems with Prolog

Setting up Prolog with Java

Executing Prolog queries using Java

Summary

Interfacing with Weka

An introduction to Weka

Installing and interfacing with Weka

Reading and writing datasets

Converting datasets

Summary

Handling Attributes

Filtering attributes

Discretizing attributes

Attribute selection

Summary

Supervised Learning

Developing a classifier

Model evaluation

Making predictions

Loading and saving models

Summary

Semi-Supervised and Unsupervised Learning

Working with k-means clustering

Evaluating a clustering model

An introduction to semi-supervised learning

The difference between unsupervised and semi-supervised learning

Self-training and co-training machine learning models

Making predictions with semi-supervised machine learning models

Summary

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Setting up Prolog with Java

Now, you will see how to download a JPL library, and how to interface with Prolog using JPL in Java.

In your browser, go to http://www.java2s.com/Code/Jar/j/Downloadjpljar.htm:

This is one of the popular repositories of all of the known JAR files that have been created, and it preserves all of those JAR files. We will get all of the information and all of the classes that are available in this JPL library, and we'll use them in our code. Click on jpl/jpl.jar.zip(27 k) to download the library. Then, you will have to extract it to get the jpl.jar file.

Once we have extracted our JAR file, we can check the code to see if it is working. Therefore, we will go to NetBeans. In NetBeans, we'll go to our project, right-click on it, and go to the Properties option. In Properties, we'll go to Libraries and the Add JAR/Folder...