Practical Artificial Intelligence Programming With Java

Practical Artificial Intelligence Programming With Java

Mark Watson
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Table of Contents

Practical Artificial Intelligence Programming With Java

  • Preface
    • Requests from the Author
    • 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 the Google Gemini Large Language Model APIs in Java
    • Java Library to Use OpenAI’s APIs
    • Example Applications
    • Wrap Up
  • 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
  • LangChain for Java as an Abstraction for Different Large Language Models
  • 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
    • Web Spidering Using the Jericho Library
    • Client for GeoNames Service
    • Wrap-up for Information Gathering
  • Resolve Entity Names to DBPedia References
    • DBPedia Entities
    • Library Implementation
    • 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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Practical Artificial Intelligence Programming With Java

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Practical Artificial Intelligence Programming With Java17 chapters

Begin ›
  1. Preface

  2. Search

  3. Using the OpenAI Large Language Model APIs in Java

  4. Using the Google Gemini Large Language Model APIs in Java

  5. Using Local LLMs Using Ollama in Java Applications

  6. LangChain for Java as an Abstraction for Different Large Language Models

  7. Anomaly Detection Machine Learning Example

  8. Genetic Algorithms

  9. Neural Networks

  10. Natural Language Processing

  11. Information Gathering

  12. Resolve Entity Names to DBPedia References

  13. Semantic Web

  14. Automatically Generating Data for Knowledge Graphs

  15. Knowledge Graph Navigator

  16. Conclusions