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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