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supervised-machine-learning

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We have a set of emails, half of which were written by one person and the other half by another person at the same company . Our objective is to classify the emails as written by one person or the other based only on the text of the email. We'll tackle this problem using Naive Bayes, SVM and Decision Tree algorithms and explore similarities and …

  • Updated Apr 22, 2017
  • Jupyter Notebook

Tutorial followed from the Understanding Machine Learning with Python pluralsight course by Jerry Kurata. Used the Machine Learning workflow to process and transform Pima Indian Diabetes data to create a prediction model that would predict which people are likely to develop diabetes with 70% or greater accuracy.

  • Updated Sep 21, 2017
  • Jupyter Notebook

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