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Machine-learning-stuff

Various usecases and models.

  1. Check out the famous # Titanic example Really good starting point on how feature engineering and selection really boost predictions and compare with cool models.

  2. Ada.m.py how I implemented from scratch Adaboost using coordinate descent on spam vs. ham data

  3. csr.ipynb demonostrates how to handle sparse data

  4. Salarypredictor

  5. implementing poly kernel svms and comparing Xvalidation accuracy spam vs. ham dataset

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Titanic kaggle comp, Spam Ham (Regressors and classifiers)

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