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
    • 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 Google Gemini’s APIs
    • Example Applications
    • Wrap Up
  • Using Local LLMs with 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
    • Why Use an Abstraction Layer?
    • Maven Project Setup
    • Implementation: The OllamaLlmLangChain4j Class
    • Prompt Templates: Two-Shot Entity Extraction
    • Test Examples
    • Running the Examples
    • Wrap Up
  • AgentScope Agent Oriented Framework.
    • Using the Java Implementation of AgentScope: Hello World
    • Using the Java Implementation of AgentScope: Tool Use
    • Wrap Up: From Simple Chat to Autonomous Tool Use
  • 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
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Practical Artificial Intelligence Programming With Java

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Practical Artificial Intelligence Programming With Java13 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 with Ollama in Java Applications

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

  7. AgentScope Agent Oriented Framework.

  8. Anomaly Detection Machine Learning Example

  9. Genetic Algorithms

  10. Neural Networks

  11. Natural Language Processing

  12. Information Gathering

  13. Resolve Entity Names to DBPedia References