Dimensionality Reduction - exercise

Introduction to Machine Learning Algorithms course - Session 4
Exercise 4
Apply the following dimensionality reduction techniques to the data:
- Filter out columns with a low variance
- Filter out one of two columns with a high linear correlation
- Replace numeric columns with principal components
- Filter out columns which are not important in predicting the target column

External resources

• Ames Housing Dataset on kaggle
• Description of the Ames Iowa Housing Data
• Seven Techniques for Data Dimensionality Reduction
• 3 New Techniques for Data-Dimensionality Reduction in Machine Learning
• Slides (Introduction to ML Algorithms course)