AI Reading List: Technologies: Technical issues
Below is a portion of my informal list of readings related to Artificial Intelligence (AI). This started out as a very short list created for use in conjunction with an academic presentation and has now grown much larger. Please let me know if you have any corrections, additions, suggestions, etc. It is very idiosyncratic and not meant to be comprehensive. Please feel free to share with others.
Artificial Intelligence (AI) Reading List, by Philip Rubin
Technologies — Technical issues:
Mayur Jain. A Deep Dive into Vector Database Algorithms. Specialized algorithms that enable efficient similarity search on billions of document embeddings. Medium, September 6, 2025.
Okan Yenigün. Recurrent Neural Networks Explained Simply. Memory in Neural Networks: Understanding RNNs. Medium, August 29, 2025.
Ryan Revilla. The First Learning Algorithms: Adaptive Filters. A brief history lesson on machine learning origins that proved to be a useful learning exercise. Medium, August 5, 2025.
Khushbu Shah. 4 Advanced Data Modelling Techniques Every Data Engineer Must Learn. Medium, July 31, 2025.
Rohit Patel. Understanding LLMs from Scratch Using Middle School Math. A self-contained, full explanation to inner workings of an LLM. Medium, Oct. 19, 2024.
Louis Chan. SHAP: Explain Any Machine Learning Model in Python. Your Comprehensive Guide to SHAP, TreeSHAP, and DeepSHAP. Medium, Jan. 11, 2023.