Practical Artificial Intelligence Programming With Clojure
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Practical Artificial Intelligence Programming With Clojure

About the Book

A practical guide to Artificial Intelligence development using Clojure that uses spaCY, transformer models, DeepLearning4J, and knowledge graph tools in Clojure applications.

About the Author

Mark Watson
Mark Watson

Mark Watson a consultant specializing in deep learning, machine learning, knowledge graphs, and general artificial intelligence software development. He uses Python, Common Lisp, Java, Clojure, Haskell, and Ruby for development.

He is the author of 23 published books on Artificial Intelligence, Deep Learning, Java, Ruby, Machine Learning, Common LISP, Clojure, JavaScript, Semantic Web, NLP, C++, Linux, and Scheme. He has 55 US Patents.

Mark's consulting customer list includes: Google, Capital One, Olive AI, CompassLabs, Disney,,, and Webmind Corporation.

web site:

Table of Contents

  • Preface
    • Clojure, With Some Java and Python
    • Personal Artificial Intelligence Journey: or, Life as a Lisp Developer
    • Acknowledgements
  • Deep Learning Using Deeplearning4j
    • Feed Forward Classification Networks
    • Optional Material: Documentation For Other Types of DeepLearning4J Built In Layers
    • Deep Learning Wrap Up
  • Natural Language Processing Using OpenNLP
    • Using the Clojure and Java Wrappers for OpenNLP
  • Python/Clojure Interoperation Using the libpython-clj Library
    • Using spaCy for Natural Language Processing
    • Using the Hugging Face Transformer Models for Question Answering
    • Combined spaCy and Transformer Question Answering
    • Using libpython-clj with the spaCy and Hugging Face Transformer Python NLP Libraries
  • Anomaly Detection Machine Learning Example
    • Motivation for Anomaly Detection
    • Math Primer for Anomaly Detection
    • AnomalyDetection Utility Class Written in Java
    • Clojure Experiment for the University of Wisconsin Cancer Data Using Java Anomaly Detection Code
  • Web Scraping
    • Web Scraping Using the jsoup Library
  • Background Material for the Semantic Web and Knowledge Graphs
    • Learning Plan
    • Available Tools
    • RDF: The Universal Data Format
    • Extending RDF with RDF Schema
    • The SPARQL Query Language
    • OWL: The Web Ontology Language
    • Semantic Web Wrap-up
  • Clojure Wrapper for the Jena RDF and SPARQL Library
  • Knowledge Graph Navigator
    • Entity Types Handled by KGN
    • KGN Implementation
  • Using the OpenAI APIs
  • Conclusions

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