The Magic of Support Vector Regression (SVR): Venturing into Higher Dimensions скачать в хорошем качестве

The Magic of Support Vector Regression (SVR): Venturing into Higher Dimensions

Step into the world of Support Vector Regression (SVR), where machine learning goes beyond straight lines! In this video, we explore the concepts of the epsilon margin, support vectors, and the powerful Kernel Trick that lets SVR work in higher dimensions. Learn how SVR’s unique loss function and kernel methods make it robust, efficient, and perfect for handling complex datasets. Whether you're new to SVR or looking to deepen your understanding, this detective-style explanation breaks it all down step by step. Don't forget to like, subscribe, and follow AlgoStalk for more algorithm adventures! ‪@AlgoStalk‬ Linear Regression:    • Linear Regression Concept (Part 1)  #linea...   Chapters 0:00 Intro 0:19 Why do we need SVR? 1:52 Margin of Tolerance and Support Vectors 2:52 SVR pros 3:41 Linear Regression Vs SVR 4:41 Regularisation and Objective Function 5:39 Kernel Function (Linear) 9:38 Poly Kernel #supportvectormachine