This is a repo where I post my python solutions to the coursera course Machine learning. The solutions can be found in the .ipynb (notebook) file in respective folder.
The way I thought that I would present my solutions is by using these notebooks. I think this is a good way to illustrate the code and my thought process when it comes to implementing these algorithms, and it gives me an opportunity to play around with the very cool notebook-concept. The instructions for the assignments can be found in the .pdf file in each folder. The GitHub for these exercises are: https://github.com/gurbraj/ML and there you can also follow the commits I've done while working through these excellent exercises. The commits more accurately describes the actual work flow for arriving to the solutions.
I learn about different algorithms by working through Kaggle problems. These notebooks can be found in the kaggle folder.