Supplementary Materials

Here are some useful links:

Course Related

• Gaussion Distribution (Normal Distribution) :Wolfram Mathworld , Wikipedia 
• Hessian: Mathworld, Wikipedia

Software/Packages

General Machine Learning Toolbox/Package

• Weka (JAVA/ GUI) : http://www.cs.waikato.ac.nz/ml/weka/ 
  • Tutorial: http://machinelearningmastery.com/how-to-run-your-first-classifier-in-weka/ 
  • Commend Line Tutorial: https://weka.wikispaces.com/Primer
• scikit-learn (Python) : http://scikit-learn.org/stable/

Linear Algebra

• Matlab:
  • Official site: https://www.mathworks.com/products/matlab.html
  • Installation : https://support.soe.ucsc.edu/software/matlab
  • Self-training :https://support.soe.ucsc.edu/software/matlab/training
  • Improve the Performance:
    • Official Guide
    • Tom Minka's tips
• Octave (An open source alternative to matlab)
  • https://www.gnu.org/software/octave/
• NumPy/SciPy/Matplotlib (Python)
  • https://www.scipy.org/
  • NumPy is for basic numerical operations. It supports numerical array (ndarray) and matrix (Be careful of the difference between these two). Tutorial: https://docs.scipy.org/doc/numpy-dev/user/quickstart.html
  • SciPy has more domain specific methods. And it supports sparse vectors/matrixs. 
  • Matplotlib is for data visualization. i.e. make the plots.  Tutorial: http://matplotlib.org/users/pyplot_tutorial.html
  • You can use some Python package manager to install the packages above:
    • pip: https://pip.pypa.io/en/stable/installing/
    • anaconda: https://www.continuum.io/downloads