CampusX Data Science Mentorship Program 2022-23 - 5 Key Points - Ridge Regression | Part 4 | Regularized Linear Models

In the final part of our Ridge Regression series we highlight 5 key points to solidify your understanding. Explore the essential takeaways that encapsulate the power and benefits of Ridge Regression, a valuable tool in the realm of regularized linear models. Code used: https://github.com/campusx-official/100-days-of-machine-learning/tree/main/day55-regularized-linear-models ============================ Do you want to learn from me? Check my affordable mentorship program at : https://learnwith.campusx.in/s/store ============================ 📱 Grow with us: CampusX' LinkedIn: https://www.linkedin.com/company/campusx-official CampusX on Instagram for daily tips: https://www.instagram.com/campusx.official My LinkedIn: https://www.linkedin.com/in/nitish-singh-03412789 Discord: https://discord.gg/PsWu8R87Z8 E-mail us at [email protected] ⌚Time Stamps⌚ 00:00 - Intro 00:46 - 5 Key Understandings about Ridge Regression 02:11 - How the coefficients get affected? 06:20 - Higher Values are impacted more 10:26 - Impact on Bias variance TradeOff 18:18 - Effect on the Loss Function 25:05 - Why Ridge Regression is called so? 29:23 - A Pratical Tip Apply Ridge Regression