Day 19: Principal Component Analysis (PCA) | Dimensionality Reduction

🔥Welcome to Day 19: Principal Component Analysis (PCA)🔥

🚀 Dive deep into the world of dimensionality reduction with this comprehensive guide to Principal Component Analysis (PCA).

🚀In this video, we'll explore:

-What is dimensionality reduction? Understand why it's crucial for dealing with high-dimensional datasets.
-Feature selection vs. feature extraction: Learn the key differences and when to use each technique.
-PCA explained: Discover how PCA works.
-Numerical example: Follow a step-by-step demonstration of PCA using a simple dataset. From standardization of dataset to computing eigen vectors and eigen values, each step is clearly explained.
-Python implementation: See how to implement PCA in Python using popular libraries like Scikit-learn.

🔥Code available: https://github.com/saif93/30-Days-of-...