My solutions to Kevin Murphy Machine Learning Book

Machine-Learning-A-Probabilistic-Perspective-Solutions

Motivation

Hey there. I am recording the solutions of the exercises of the fourth printing of this book in this repository. The only exercises that I do not intend to do in this first run are those which explicit require MATLAB. Any computational exercise will be done in Python using a Jupyter notebook. I will follow a schema where I give a introduction and some insight into the problem, solve it and then make some remarks on the solution. I strongly reccomend the reading of the Intro and Conclusion section of the exercises that you’re interested in. I intend to update the solutions in a reasonable pace, starting now (January 2017).

I hope this might help anyone who has an interest in the book and Machine Learning as a whole. If you have any question, want to debate about the book, or think that some solution may be wrong or could be improved, feel free to send me an e-mail at: arthurzc23@gmail.com.

Updates (20/03/2017)

Hello guys, I am finally back. During my break some people contacted me about the future of the repository and I want to share with all what I’ve told them. The repository goal is to give a solution manual for the whole book. I believe this semester I will finish Chapters 4, 5, 6 and maybe 7. I will try to post the exercises more frequently, but keep in mind that this is not my main priority at the moment.

New decisions

• As I read the book, I am facing new concepts that were useful to explain questions of previous chapters. However, due to time constraints, I do not intend to update the exercises with those new insights in the near future, save extraordinary cases.

About the author

I am a brazilian Electrical Engineer graduated at Unicamp, one the most prestigious universities in my country. I graduated as the best student of my class in 2016, among other honors. Currently, I am a M.S. student on the Electrical Engineering program at the same University, where I intend to use machine learning in agriculture and food/beverage problems.