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Support Vector Machines - A Friendly Introduction

Serrano.Academy via YouTube

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Overview

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This beginner-friendly course introduces support vector machines visually with little mathematics. It explains classification boundaries, margins, the perceptron-based training process, gradient descent, and how the C parameter balances classification and margin errors.

Syllabus

Introduction
Classification goal: split data
Perceptron algorithm
Split data - separate lines
How to separate lines?
Expanding rate
Perceptron Error
SVM Classification Error
Margin Error
Challenge - Gradient Descent
Which line is better?
The C parameter
Series of 3 videos
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Taught by

Serrano.Academy

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