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In the second part of our series, we break down the mathematical formulation of Ridge Regression and guide you through coding it from scratch. Explore the essence of Ridge Regression, a form of regularized linear models, and gain hands-on experience in implementing this advanced regression technique. Code : https://github.com/campusx-official/100-days-of-machine-learning/tree/main/day55-regularized-linear-models Matrix Differentiation : http://www.gatsby.ucl.ac.uk/teaching/courses/sntn/sntn-2017/resources/Matrix_derivatives_cribsheet.pdf Videos to watch: https://www.youtube.com/watch?v=dXHIDLPKdmA https://www.youtube.com/watch?v=NU37mF5q8VE Sklearn Ridge Class: https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.Ridge.html ============================ 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 00:32 - Revision on Ridge Regression 12:27 - Code Demo 20:50 - Ridge Regression for N-Dimensional Data 33:46 - Coding ridge regression from scratch
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