Dimensionality Reduction in Python

Description

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.

Syllabus :

• Exploring high dimensional data
• Feature selection I, selecting for feature information
• Feature selection II, selecting for model accuracy
• Feature extraction