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Lesson 2 - Logistic Regression for Classification

Machine Learning with Python: Zero to GBMs

Logistic regression is a commonly used technique for solving binary classification problems. The following topics are covered in this lesson:

  • Downloading a real-world dataset from Kaggle
  • Splitting a dataset into training, validation & test sets
  • Imputing and scaling numeric features
  • Encoding categorical columns as one-hot vectors
  • Training a logistic regression model using Scikit-learn
  • Evaluating a model using a validation set and test set

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