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SUPPORTING MATERIAL

Dynamic e-Chapters

As a free service to our readers, we are introducing e-Chapters that cover new topics that are not covered in the book. These chapters are dynamic and will change with new trends in Machine Learning. New chapters will be added as time permits.

To access the e-Chapters, go to the book forum e-Chapter section:

  • User Name: bookreaders
  • Password: Enter the first word on page 27 of the book.

Enjoy!

Slides

Lecture slides based on the book and the e-chapters are available here. They are designed for quarter-length and semester-length courses that use the book as a text.

Discussion

You can read the discussion of the book by our readers on the book forum If you would like to contribute to the discussion, please register there.

Video Lectures

Video lectures covering different parts of the book will be posted. The first set of lectures is based on the Learning From Data course. The lectures are available here.

Code

Students in courses and readers of the book have implemented the examples and exercises in a variety of languages, including MATLAB, R, OCTAVE, PYTHON, JAVA, C++. Some publicly-available implementations are as follows.

LIONoso

Various cases in the book can be implemented with LIONoso, a comprehensive Machine Learning and Intelligent Optimization tool for non-profit research and academic use. Some cases that support the presentation in the book are publicly available online at:

LIONoso for "Learning from data"

Octave

Data

Handwritten Digits

The digits data are useful data for experimenting with some of the techniques discussed in the book, and they are also used in some of the chapter problems.

Raw Data (info)

sample digit images

sample digit sample digit sample digit sample digit sample digit sample digit sample digit sample digit sample digit
Data processed into intensity and symmetry features

scatter plot of features

scatter plot