Practical Python Artificial Intelligence Programming

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Artificial Intelligence programming with Python. Covers both theory and practical examples of LLMs, deep learning, symbolic AI, and Knowledge Representation

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Practical Python Artificial Intelligence Programming30 chapters

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  1. Cover Material, Copyright, and License

  2. Preface

  3. Python Development Environment

  4. Part 1 - Machine Learning

  5. “Classic” Machine Learning

  6. Regression and Clustering

  7. Exploratory Data Analysis and Feature Engineering

  8. Anomaly Detection

  9. Part 2 - Deep Learning

  10. The Basics of Deep Learning

  11. Natural Language Processing Using Deep Learning

  12. Part IV - Overviews of Image Generation, Reinforcement Learning, and Recommendation Systems

  13. Overview of Image Generation

  14. Categorical Deep Learning: From Axioms to Implementation using Category Theory

  15. Overview of Reinforcement Learning (Optional Material)

  16. Overview of Recommendation Systems (Optional Material)

  17. Part 3 - Large Language Models

  18. Introduction to Transformers and Large Language Models

  19. LLMs with Public APIs

  20. LLMs with Local Models

  21. Text Adventure Game with an LLM Game Master

  22. Semantic Web Question Answering with SPARQL and Large Language Models

  23. Part 4 - Symbolic AI and Knowledge Representation

  24. Symbolic AI

  25. Expert Systems Using the Rete Algorithm

  26. A Chess Engine and AI Player in Pure Python

  27. Part 5 - Knowledge Representation

  28. Getting Setup To Use Graph and Relational Databases

  29. Optional Material: A Deeper Dive Into Semantic Web and Linked Data

  30. Open Knowledge Format (OKF) for Human-Agent Systems