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In the third installment of our series, we delve into Ridge Regression with a focus on Gradient Descent. Explore how this optimization technique plays a crucial role in implementing Ridge Regression, a powerful form of regularized linear models. 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=NU37mF5q8VE ============================ 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]
