Mathematics for Machine Learning - 2020

Details

Title : Mathematics for Machine Learning Author(s): Deisenroth, Marc P. and Faisal, A. Aldo and Ong, Cheng Soon Link(s) : https://mml-book.github.io/book/mml-book.pdf

Rough Notes

Chapter 1: Introduction and Motivation

Main concepts in this book:

  • Data can be represented as vectors.
  • Appropriate models are important, and can be chosen using a probabilistic or optimization view.
  • Learning from available data can be done with numerical optimization algorithms, and the aim is to make the model perform well on unseen data.

[Figure 1.1 summarizes the book contents nicely].

Chapter 2:

Emacs 29.4 (Org mode 9.6.15)