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.
datasets: contains all the sample datasets which are used in the scripts.scripts: contains the solutions in Python.plots: folder having some plots of the datasets and their respective hypothesis.
- Switch to the parent directory.
cd <path-to-ml-exercises>- 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- (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.
- Plot of Logistic regression classifier with regularization and the computed decision boundary (exercise 2, data 2).
