In this course, you will :
- Learn the distinction between feature selection and feature extraction and how to use both techniques for data exploration.
- Discover the curse of dimensionality and how dimensionality reduction can assist you in overcoming it.
- You will be introduced to a variety of techniques for detecting and removing features that add little value to the dataset.
- Discover how to use models to find the most important features in a dataset for predicting a specific target feature.
- You'll gain an understanding of how and why this algorithm is so powerful, and you'll use it for data exploration as well as data pre-processing in a modelling pipeline.
- Exploring high dimensional data
- Feature selection I, selecting for feature information
- Feature selection II, selecting for model accuracy
- Feature extraction