Collection of notebooks on machine learning topics:

  • Introduction to Python and Numpy
  • Classification: kNN, Logistic regression, Support Vector Machines
  • Regression: kNN, Least Squares, Bayesian Inference, Gaussian Processes
  • Clustering: k-means, Spectral Clustering
  • Topic Modeling

Most of the notebooks above rely on the popular Python libraries for machine learning Scikit-learn and MLLib.

Machine Learning for all (ML4all)
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