ashishraste / ml-exercises Goto Github PK

The exercise problems are taken from Andrew Ng's Machine Learning MOOC. I look forward to add more problem sets from other sources in future.

1. datasets : contains all the sample datasets which are used in the scripts.
2. scripts : contains the solutions in Python.
3. plots : folder having some plots of the datasets and their respective hypothesis.

1. Switch to the parent directory.
   

cd <path-to-ml-exercises>

2. Run a script from this directory. This makes sure that the paths of the dataset-files supplied to the scripts are consistent.
   

python scripts/<script-name>.py

3. (Optional) If you'd like to have pretty XKCD-style graphs, you can un-comment plt.xkcd() statements in the scripts.
   More information about setting XKCD-style font for your system could be found here.

1. Plot of Logistic regression classifier with regularization and the computed decision boundary (exercise 2, data 2).