Practical Artificial Intelligence Development With Racket

Mark Watson

Table of Contents

Preface
Tutorial and Using Datastores
A Quick Racket Tutorial
Datastores
Implementing a Simple RDF Datastore With Partial SPARQL Support in Racket
Webscraping and Browser Use
Web Scraping
Interfacing with External Programs: A Lightpanda Browser Client
Large Language Models
Building a MicroGPT in Racket
Using the Google Gemini, OpenAI, Anthropic, Mistral, and Local Large Language Model APIs in Racket
Ollama Tools/Function Calling in Racket
A Racket Coding Agent
Retrieval Augmented Generation of Text Using Embeddings
Agentic RAG Using the Gemini API
Deep Learning, Natural Language Processing and Knowledge Graphs
Deep Learning in Racket with Malt: From XOR to a Two-Tower Recommendation System
Category-Theory Deep Learning in Racket
Reinforcement Learning in Racket: Bandits, Q-Learning, Policy Gradients and DQN
Natural Language Processing
- NLP Wrap Up
- Optional Practice Problems
Knowledge Graph Navigator
Rule Based Symbolic AI Systems
Implementing OPS5 in Racket: A Forward-Chaining Production System
Logic Programming with Racklog: Two Classic Problems Revisited
Miscellaneous Short and Interesting Projects
Computing Pi and e: Fourteen Classical Algorithms in Exact Arithmetic
Conclusions

Tutorial and Using Datastores

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A Quick Racket Tutorial