A Tutorial on Simple Machine Learning Methods Held for the Graduate School on Bionics, 2012.
Created by Hannes Schulz, Andreas Mueller and Nenard Birešev.
The slides are at
The interactive notebooks are in the main folder.
Viewing the notebooks online
The content of the notebooks can be viewed online through nbviewer.ipython.org. This is not interactive. You need to install Python on your computer to use the notebooks interactively.
- 0 - Python Intro.ipynb
- 1 - PCA.ipynb
- 2 - KMeans.ipynb
- 3a - Linear regression 1D.ipynb
- 3b - Linear regression 2D.ipynb
- 4 - Logistic Regression.ipynb
- 5 - k Nearest Neighbors.ipynb
- The latex source code for the slides is contained in
- The notebooks used to generating some of the figures on the slides is in
For a true interactive use of the notebooks you need to install Python, IPython (for notebooks) and the required libraries scikit-learn, matplotlib and numpy.
You can install everything at once using a complete scientific Python distribution. Two good ones are the Enthought Python distribution (EPD, free for academic use) or Python-(x, y) (free for everyone).
Just use your package manager, for example on ubuntu or debian, use
apt-get install python ipython python-matplotlib python-numpy python-sklearn.
You need to make sure to have at least IPython >= 0.11 installed. You can update using the programm
More tips on installing scikit-learn can be found on the scikit-learn website.