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 Programming27 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. Overview of Reinforcement Learning (Optional Material)

  15. Overview of Recommendation Systems (Optional Material)

  16. Part 3 - Large Language Models

  17. Introduction to Transformers and Large Language Models

  18. LLMs with Public APIs

  19. LLMs with Local Models

  20. Text Adventure Game with an LLM Game Master

  21. Part 4 - Symbolic AI and Knowledge Representation

  22. Symbolic AI

  23. Expert Systems Using the Rete Algorithm

  24. Part 5 - Knowledge Representation

  25. Getting Setup To Use Graph and Relational Databases

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

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