Book Website (2nd Edition)

This is the website for the 2nd edition (2024). The website for the previous 1st Edition is located here.

“The coverage is very unique and I like the way that the theory is interspersed with applications and python scripts. I don’t know any other book that covers ML in such an integrated manner.”
— Alfred Hero, Professor, University of Michigan, USA

“I think the selection of topics is really nice. Also, the math is very clearly written; I’m sure it will be greatly appreciated.”
— Gábor Lugosi, Research Professor, Pompeu-Fabra University, Spain

SpringerLink | Google Books | Amazon

All typos in the previous edition have been corrected. There is a new chapter 12 on physics-informed machine learning, as well as new material on deep neural network in Chapters 6 and 11.

Book front matter
Book back matter (including all appendices)
Book errata
Data sets used in the book

Chapter 1 Introduction: Lecture slides | Figures | Python scripts

Chapter 2 Optimal Classification: Lecture slides | Figures | Python script

Chapter 3 Sample-Based Classification: Lecture slides | Figures

Chapter 4 Parametric Classification: Lecture slides | Figures

Chapter 5 Nonparametric Classification: Lecture slides | Figures | Python scripts

Chapter 6 Function-Approximation Classification: Lecture slides | Figures | Python scripts

Chapter 7 Error Estimation for Classification: Lecture slides | Figures | Python scripts

Chapter 8 Model Selection for Classification: Lecture slides | Figures

Chapter 9 Dimensionality Reduction: Lecture slides | Figures | Python scripts

Chapter 10 Clustering: Lecture slides | Figures | Python scripts

Chapter 11 Regression: Lecture slides | Figures | Python scripts

Chapter 12 Physics-Informed Machine Learning: Lecture slides | Figures | Python jupyter notebooks

Appendix: Figures | Python script

Note: The lecture slides do not include material from the starred or additional topics sections.

An instructor’s manual with problem solutions can be obtained by contacting the publisher or e-mailing the author using an institutional e-mail address.
Please send corrections, comments, and suggestions to ulisses@tamu.edu