Some books and information on machine learning and AI

General introduction (without math)

• 簡禎富，工業3.5：台灣企業邁向智慧製造與數位決策的戰略，天下雜誌，2019
• Alex J. Gutman and Jordan Goldmeier, Becoming a Data Head: How to Think, Speak, and Understand Data Science, Statistics, and Machine Learning, Wiley, 2021.

工業工程總結實踐

建議

作業與資訊 (Homework and Information)

Tabular foundation model

Hollmann, N., Müller, S., Purucker, L. et al. Accurate predictions on small data with a tabular foundation model. Nature 637, 319–326 (2025). https://doi.org/10.1038/s41586-024-08328-6 (Code)

The most-cited papers of the twenty-first century

Helen Pearson, Heidi Ledford, Matthew Hutson & Richard Van Noorden, Exclusive: the most-cited papers of the twenty-first century: A Nature analysis reveals the 25 highest-cited papers published this century and explores why they are breaking records, Nature, 15 April 2025. (Supplementary information)

Papers in AI:

Adaptive Forests For Classification

D. Bertsimas and Y. Cui, Adaptive Forests For Classification, arXiv:2510.22991, 2025. (code)