Python Solutions for Andrew Ng's Machine Learning Coursera Course. This is work in progress.
Professor Ng's course definitely provides more in depth material compared to many other online courses as it shows more under the hood mechanics behind Machine Learning methods. I also understand why he chose to use Octave, but I wanted to practice my Python knowledge. Coursera also has provided a lot of the codes as scripts to run and I tried to recreate these scripts in Python. I have also utilized the methods and code provided by @kaleko and @johnwittenauer.
Keep in mind that this solution manual is written to practice my computing skills and document my learning progress. I tried to aim for brevity when I could but this was not always the case. In this sense my work can be more useful for people who just started their journey into programming and Machine Learning. Or not.