Practical Artificial Intelligence Programming With Java
Practical Artificial Intelligence Programming With Java
Sixth Edition (February 2023)
About the Book
This book covers a variety of topics dealing with Artificial Intelligence, Neural Networks and Deep Learning, Information Gathering, and two new chapters on the Semantic Web (and one previous chapter on the Semantic Web that has been heavily modified)
The book example code is dual licenced under the Apache 2 and GPL 3 licenses. You may want to look at the book example programs at the github repository for this book before purchasing this book.
All of my Leanpub books, including this book, can be read for FREE on my web site: https://markwatson.com/
About the Author
Table of Contents
-
Preface
- Personal Artificial Intelligence Journey
- Maven Setup for Combining Examples in this Book
- Software Licenses for Example Programs in this Book
- Acknowledgements
-
Search
- Representation of Search State Space and Search Operators
- Finding Paths in Mazes
- Finding Paths in Graphs
- Adding Heuristics to Breadth-first Search
- Heuristic Search and Game Playing: Tic-Tac-Toe and Chess
-
Using the OpenAI Large Language Model APIs in Java
- Java Library to Use OpenAI’s APIs
- Example Applications
- Extraction of Facts and Relationships from Text Data
- Using LLMs to Summarize Text
-
Using Local LLMs Using Ollama in Java Applications
- Advantages of Using Local LLMs with Ollama
- Applications of Local LLMs with Ollama
- Java Library to Use Ollama’s REST API
- Example Using the Library
- Extraction of Facts and Relationships from Text Data
- Using LLMs to Summarize Text
-
Anomaly Detection Machine Learning Example
- Motivation for Anomaly Detection
- Math Primer for Anomaly Detection
- AnomalyDetection Utility Class
- Example Using the University of Wisconsin Cancer Data
-
Genetic Algorithms
- Theory
- Java Library for Genetic Algorithms
- Finding the Maximum Value of a Function
-
Neural Networks
- Road Map for the Neural Network Example Code
- Backpropagation Neural Networks
- A Java Class Library for Back Propagation
- Adding Momentum to Speed Up Back-Prop Training
- Wrap-up for Neural Networks
-
Natural Language Processing
- Overview of the NLP Library and Running the Examples
- Tokenizing, Stemming, and Part of Speech Tagging Text
- Named Entity Extraction From Text
- Automatically Assigning Categories to Text
- Text Clustering
- Wrapup
-
Information Gathering
- Web Scraping Examples
- Client for GeoNames Service
- Wrap-up for Information Gathering
-
Resolve Entity Names to DBPedia References
- DBPedia Entities
- Wrap-up for Resolving Entity Names to DBPedia References
-
Semantic Web
- Available Tools
- Relational Database Model Has Problems Dealing with Rapidly Changing Data Requirements
- RDF: The Universal Data Format
- Extending RDF with RDF Schema
- The SPARQL Query Language
- Using Jena
- OWL: The Web Ontology Language
- Semantic Web Wrap-up
-
Automatically Generating Data for Knowledge Graphs
- Implementation Notes
- Generating RDF Data
- KGCreator Wrap Up
-
Knowledge Graph Navigator
- Entity Types Handled by KGN
- General Design of KGN with Example Output
- UML Class Diagram for Example Application
- Implementation
- Wrap-up
- Conclusions
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