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My solutions for the CaltechX Learning From Data course on edX.
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Update README.md 		2017-12-21 21:56:26 -02:00
extra/neural-networks Simple (but hopefully clean) implementation of backpropagation. 2013-12-13 20:45:21 -02:00
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README.md Update README.md 2017-12-21 21:56:26 -02:00

README.md

Learning From Data - Solutions

This is the code/math I wrote in order to solve most of the assignments of Learning From Data, a machine learning course by Caltech.

Disclaimer: Don't follow this material blindly, it might be wrong. Use your judgement.

A Note About The Honor Code

The solutions were released incrementally, one assignment at a time, after each deadline. According to the course staff, this is ok; in fact, the professor himself encourages the students to show their solutions.

To fully enjoy the course, do not look at the solutions provided here until you submit your answer.

Requirements

How The Assignments Are Organized

Solutions for each week's homework are kept in its own directory. Each directory contains a README file that explains the main purpose of the homework along with the following subdirectories:

/img
Figures and plots generated during my thinking process
/math
Explanations and solutions involving math
/src
Octave code that answers the more practical questions

Donate

If this project is useful for you, buy me a beer!

Bitcoin: bc1qtwyfcj7pssk0krn5wyfaca47caar6nk9yyc4mu

License

Code And Plots

Copyright (C) Daniel Fernandes Martins. Distributed under the New BSD License.

Homework Assignments

Copyright (C) Yaser Abu-Mostafa. All rights reserved.