L - 2.10 : Ridge Regression Explained Simply | Regularization Explained with Examples in ML

Описание: #ridgeregression #machinelearning #regularization
Ridge Regression is one of the most confusing topics in Machine Learning — but it doesn’t have to be
In this video, I explain Ridge Regression from scratch in the simplest possible way, focusing on intuition + clarity, not memorization

🔍 What you’ll learn in this video:

1. What is Ridge Regression and how it works
2. Why Ordinary Least Squares (OLS) regression fails in real-world data
3. The problem of multicollinearity
4. How L2 regularization helps control model complexity
5. Why standardization is mandatory in Ridge Regression
6. How Ridge Regression improves model stability and generalization

This video is specially designed for:

Students learning Machine Learning / Data Science
Beginners struggling with regularization techniques
Exam & interview preparation (GATE, university exams, placements)
Anyone confused about why and when to use Ridge Regression

📌 If linear regression is overfitting your data, this video will change how you look at models

👉 Watch till the end to fully understand why standardization plays a critical role in Ridge Regression

📚 Part of my Machine Learning Playlist
(Simple explanations | Strong intuition | Real understanding)

If this video helps you, don’t forget to like, share, and subscribe — it really helps the channel reach more learners worldwide 🌍

#LinearRegression #DataScience #nikitajaininsights #MachineLearningTutorial #MLForBeginners #L2Regularization #regressionanalysis
If you like the video do like and share the video and subscribe my channel.
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