Practical Artificial Intelligence Development With Racket

Course overview

27 chapters
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Practical Artificial Intelligence Development With Racket27 chapters

Begin
  1. Preface

  2. Tutorial and Using Datastores

  3. A Quick Racket Tutorial

  4. Datastores

  5. Implementing a Simple RDF Datastore With Partial SPARQL Support in Racket

  6. Webscraping and Browser Use

  7. Web Scraping

  8. Interfacing with External Programs: A Lightpanda Browser Client

  9. Large Language Models

  10. Building a MicroGPT in Racket

  11. Using the Google Gemini, OpenAI, Anthropic, Mistral, and Local Large Language Model APIs in Racket

  12. Ollama Tools/Function Calling in Racket

  13. A Racket Coding Agent

  14. Retrieval Augmented Generation of Text Using Embeddings

  15. Agentic RAG Using the Gemini API

  16. Deep Learning, Natural Language Processing and Knowledge Graphs

  17. Deep Learning in Racket with Malt: From XOR to a Two-Tower Recommendation System

  18. Category-Theory Deep Learning in Racket

  19. Reinforcement Learning in Racket: Bandits, Q-Learning, Policy Gradients and DQN

  20. Natural Language Processing

  21. Knowledge Graph Navigator

  22. Rule Based Symbolic AI Systems

  23. Implementing OPS5 in Racket: A Forward-Chaining Production System

  24. Logic Programming with Racklog: Two Classic Problems Revisited

  25. Miscellaneous Short and Interesting Projects

  26. Computing Pi and e: Fourteen Classical Algorithms in Exact Arithmetic

  27. Conclusions