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Included book type to two listings in the Artificial Intelligence section
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books/free-programming-books-subjects.md

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@@ -150,15 +150,15 @@ Books that cover a specific programming language can be found in the [BY PROGRAM
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* [Clever Algorithms Nature-Inspired Programming Recipes](https://bjpcjp.github.io/pdfs/ruby/Clever-Algorithms.pdf) - Jason Brownlee (PDF) (CC BY-NC-SA)
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* [Generative AI in Higher Education: The ChatGPT Effect](https://www.taylorfrancis.com/books/oa-mono/10.4324/9781003459026/generative-ai-higher-education-cecilia-ka-yuk-chan-tom-colloton) - Cecilia Ka Yuk Chan, Tom Colloton (PDF) (CC BY)
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* [Getting Started with Artificial Intelligence , 2nd Edition](https://www.ibm.com/downloads/cas/OJ6WX73V) - Tom Markiewicz, Josh Zheng (PDF)
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* [Graph Representational Learning Book](https://www.cs.mcgill.ca/~wlh/grl_book/) - William L. Hamilton
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* [Graph Representational Learning Book](https://www.cs.mcgill.ca/~wlh/grl_book/) - William L. Hamilton (PDF)
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* [How Transformer LLMs Work](https://www.deeplearning.ai/short-courses/how-transformer-llms-work/) - Jay Alammar, Maarten Grootendorst (DeepLearning.AI)
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* [Hugging Face LLM Course](https://huggingface.co/learn/llm-course/en/chapter1/1) (HTML)
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* [Introduction to Autonomous Robots](https://github.com/correll/Introduction-to-Autonomous-Robots/releases) - Nikolaus Correll (PDF) (CC BY-NC-ND)
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* [Large Language Models from Scratch](https://www.youtube.com/watch?v=lnA9DMvHtfI) - freeCodeCamp (YouTube)
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* [Machine Learning For Dummies®, IBM Limited Edition](https://www.ibm.com/downloads/cas/GB8ZMQZ3) - Daniel Kirsch, Judith Hurwitz (PDF)
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* [Mastering Generative AI and Prompt Engineering: A Practical Guide for Data Scientists](https://datasciencehorizons.com/pub/Mastering_Generative_AI_Prompt_Engineering_Data_Science_Horizons_v2.pdf) - Data Science Horizons (PDF)
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* [On the Path to AI: Law’s prophecies and the conceptual foundations of the machine learning age](https://link.springer.com/book/10.1007/978-3-030-43582-0) - Thomas D. Grant, Damon J. Wischik (PDF, EPUB)
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* [Paradigms of Artificial Intelligence Programming: Case Studies in Common Lisp](https://github.com/norvig/paip-lisp) - Peter Norvig
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* [Paradigms of Artificial Intelligence Programming: Case Studies in Common Lisp](https://github.com/norvig/paip-lisp) - Peter Norvig (Git repo)
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* [Probabilistic Programming & Bayesian Methods for Hackers](https://camdavidsonpilon.github.io/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/) - Cam Davidson-Pilon (HTML, Jupyter Notebook)
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* [Stanford CS224N: Natural Language Processing with Deep Learning](https://www.youtube.com/playlist?list=PLoROMvodv4rOSH4v6133s9LFPRHjEmbmJ) - Christopher Manning (Stanford Online)
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* [The History of Artificial Intelligence](https://courses.cs.washington.edu/courses/csep590/06au/projects/history-ai.pdf) - Chris Smith, Brian McGuire, Ting Huang, Gary Yang (PDF)

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