Name: Feature extraction - Principal Component selection
Uploaded: 2020-01-13T00:00:00Z
Description: This chapter is a deep-dive on the most frequently used dimensionality reduction algorithm, Principal Component Analysis (PCA). You'll build intuition on how and why this algorithm is so powerful and will apply it both for data exploration and data pre-processing in a modeling pipeline. You'll end with a cool image compression use case.