Machine learning exercises done in Python
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README.md

Machine Learning in Python

These are completed homework exercises from Andrew Ng's Coursera course on Machine Learning, except instead of using Matlab/Octave as required by the course, I've done the exercises in Python. If the exercise called for writing one's own routine or function in Octave, I generally tried to do the same think with pandas and numpy and then do it a third time using scikit-learn. Sometimes this meant rewriting some of the provided Octave routines.

  1. Linear Regression
  2. Logistic Regression
  3. Multiclass Classification and Neural Networks
  4. Neural Networks
  5. Regularized Linear Regression and Bias vs. Variance
  6. Support Vector Machines
  7. K-means Clustering and Principal Component Analysis
  8. Anomaly Detection and Recommender Systems