Contrarian/hype-debunking
General
Fuzzy Logic
Expert Systems
Large Language Models
- "On the Biology of a Large Language Model": "We investigate the internal mechanisms used by Claude 3.5 Haiku — Anthropic's lightweight production model — in a variety of contexts, using our circuit tracing methodology."
Natural Language Processing
Machine Learning
- A Brief Introduction to Machine Learning for Engineers - Osvaldo Simeone (PDF)
- A Brief Introduction to Neural Networks
- A Comprehensive Guide to Machine Learning - Soroush Nasiriany, Garrett Thomas, William Wang, Alex Yang (PDF)
- A Course in Machine Learning (PDF)
- A First Encounter with Machine Learning - Max Welling (PDF) (:card_file_box: archived)
- A Selective Overview of Deep Learning - Fan, Ma, and Zhong (PDF)
- Algorithms for Reinforcement Learning - Csaba Szepesvári (PDF)
- An Introduction to Statistical Learning - Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani (PDF)
- Approaching Almost Any Machine Learning Problem - Abhishek Thakur (PDF)
- Bayesian Reasoning and Machine Learning
- Deep Learning - Ian Goodfellow, Yoshua Bengio and Aaron Courville
- Deep Learning for Coders with Fastai and PyTorch - Jeremy Howard, Sylvain Gugger (Jupyter Notebooks)
- Deep Learning with PyTorch - Eli Stevens, Luca Antiga, Thomas Viehmann (PDF)
- Dive into Deep Learning
- Explorations in Parallel Distributed Processing: A Handbook of Models, Programs, and Exercises - James L. McClelland
- Foundations of Machine Learning, Second Edition - Mehryar Mohri, Afshin Rostamizadeh, Ameet Talwalkar
- Free and Open Machine Learning - Maikel Mardjan (HTML)
- Gaussian Processes for Machine Learning
- IBM Machine Learning for Dummies - Judith Hurwitz, Daniel Kirsch
- Information Theory, Inference, and Learning Algorithms
- Interpretable Machine Learning - Christoph Molnar
- Introduction to CNTK Succinctly - James McCaffrey
- Introduction to Machine Learning - Amnon Shashua
- Keras Succinctly - James McCaffrey
- Learn Tensorflow - Jupyter Notebooks
- Learning Deep Architectures for AI (PDF)
- Machine Learning
- Machine Learning for Data Streams - Albert Bifet, Ricard Gavaldà, Geoff Holmes, Bernhard Pfahringer
- Machine Learning from Scratch - Danny Friedman (HTML, PDF, Jupyter Book)
- Machine Learning, Neural and Statistical Classification
- Machine Learning with Python - Tutorials Point (HTML, PDF)
- Mathematics for Machine Learning - Garrett Thomas (PDF)
- Mathematics for Machine Learning - Marc Peter Deisenroth, A Aldo Faisal, and Cheng Soon Ong
- Neural Networks and Deep Learning
- Practitioners guide to MLOps - Khalid Samala, Jarek Kazmierczak, Donna Schut (PDF)
- Probabilistic Models in the Study of Language (Draft, with R code)
- Python Machine Learning Projects - Lisa Tagliaferri, Brian Boucheron, Michelle Morales, Ellie Birkbeck, Alvin Wan (PDF, EPUB, Kindle)
- Reinforcement Learning: An Introduction - Richard S. Sutton, Andrew G. Barto (PDF)
- Speech and Language Processing (3rd Edition Draft) - Daniel Jurafsky, James H. Martin (PDF)
- The Elements of Statistical Learning - Trevor Hastie, Robert Tibshirani, and Jerome Friedman
- The LION Way: Machine Learning plus Intelligent Optimization - Roberto Battiti, Mauro Brunato (PDF)
- The Mechanics of Machine Learning - Terence Parr and Jeremy Howard
- The Python Game Book - Horst Jens (:card_file_box: archived)
- Top 10 Machine Learning Algorithms Every Engineer Should Know - Binny Mathews and Omair Aasim
- Understanding Machine Learning: From Theory to Algorithms - Shai Shalev-Shwartz, Shai Ben-David
Coding Assistants/Interaction
Retrieval-Augmented Generation (RAG)
Tags:
reading
ai
machine learning
fuzzy logic
logic
expert system
nlp
Last modified 02 July 2025