Artificial intelligence, which is becoming increasingly relevant in the modern world, where everything is driven by technology and data, is the process of automating any system or process to carry out complex tasks and functions automatically in order to achieve optimal productivity.
Hands-On Artificial Intelligence with Java for Beginners explains the basics of AI using popular Java-based libraries and frameworks to build your smart applications.
Hands-On Artificial Intelligence with Java for Beginners is for Java developers who want to learn the fundamentals of artificial intelligence and extend their programming knowledge to build smarter applications.
Chapter 1, Introduction to Artificial Intelligence and Java, introduces artificial intelligence. It gives a very brief introduction to artificial intelligence, and how we can install and work with Java.
Chapter 2, Exploring Search Algorithms, will introduces two basic search techniques—Dijkstra's algorithm and the A* algorithm.
Chapter 3, AI Games and Rule-Based System, discusses game playing, how game playing works, how we can implement game playing in Java, what rule-based systems are, how we can implement a rule-based system, and how we can perform interfacing with rule-based systems in Java. We'll implement a rule-based system in Prolog and we'll perform the interfacing of Prolog with Java.
Chapter 4, Interfacing with Weka, discusses how to interact with Weka and how to perform interfacing with Weka, so the chapter covers how to download Weka and how to work with datasets.
Chapter 5, Handling Attributes, explains how to handle attributes while developing different kinds of classifiers and clusters. We'll also learn about different techniques for filtering attributes.
Chapter 6, Supervised Learning, shows how supervised models are trained, how we can develop a classifier, how we can perform evaluation on a classifier, and how we can make predictions on a classifier.
Chapter 7, Semi-Supervised and Unsupervised Learning, explains the differences between a supervised learning model and a semi-supervised learning model, and we'll implement a semi-supervised model.
The prerequisites for this book are that you should have an understanding of AI, you should have taken a course on AI, and you should have a working knowledge of Java.
This book has the following software requirements:
- NetBeans 8.2
- Weka 3.8
- SWI-Prolog 7.2-7.6
This course has been tested on the following system configurations:
- OS: Windows 7, Windows 10, macOS, Ubuntu Linux 16.04 LTS
- Processor: Dual core 3.0 GHz
- Memory: 4 GB
- Hard disk space: 200 MB
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