15. Lasso Regression & Elastic Net Explained | L1 vs L2 Regularization | Feature Selection in ML

In this video, I explain Lasso Regression and Elastic Net Regression in a clear and intuitive way.

You’ll understand:

What Lasso Regression (L1 Regularization) is

How Elastic Net Regression combines L1 and L2 penalties

Why feature selection happens in Lasso

Difference between Ridge, Lasso, and Elastic Net

When to use Elastic Net instead of Lasso or Ridge

Effect of lambda (α) on model coefficients

Real-world intuition behind regularization

This video is ideal for:

Machine Learning beginners

Data Science students

Interview preparation (ML / Data Science)

Anyone confused about regularization techniques

📌 Watch till the end to clearly understand why Elastic Net is useful when features are correlated.

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