Recently, I got acquainted with people from a certain AI startup, and engineers who are actively using machine learning in their work recommended some introductory books for machine learning, so I’d like to share them.

Me: “If you have any recommended books or sites for getting started with machine learning, please let me know ✌️”

ML Person: “The overwhelmingly recommended introduction is (continued in the main text below)”

Machine Learning Introductory Books

Practical Introduction to Machine Learning

The overwhelmingly recommended introduction is “Programming Collective Intelligence”.

It’s Python 2, but you actually implement machine learning algorithms in Python using APIs while understanding them. It’s more practical than theoretical, so you can learn quickly.

Theoretical Introduction to Machine Learning

If you prefer theory, either of the following books. They’re often used as university textbooks.

○○ University used “First Pattern Recognition”, but I feel “Easy-to-Understand Pattern Recognition” is easier to understand.

PRML is High Difficulty

There’s also PRML, but I think it’s hard to read at first, so I recommend starting with the above.

• Pattern Recognition and Machine Learning Volume 1
• Pattern Recognition and Machine Learning Volume 2 (Statistical Prediction by Bayesian Theory)
• PRML - Machine Learning "Toki no Mori Wiki"

I’ll also start learning machine learning so I can implement it practically.

That’s all from the Gemba.