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MLDS

Machine Learning Data Science

A collection of random bits and bobs accumulated over time. This isn't specific to any project. Code and docs are related to random activites, videos, courses, hackathons, personal projects etc.

Have a look in the visualisations folder for some neat looking results.

A look into a variety of models

Logistic Regression

  • p(y=1|x) = sigma(w-transpose x)
  • Linear classification model
  • Can handle sparse data
  • Fast to train
  • Weights can be interpreted