Machine Learning A-Z: Support Vector Machine with Python ©
Learn machine learning and support vector machine from scratch
Updated on Apr, 2024
Language - English
Lectures -68
Duration -11 hours
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Course Description
This course is designed for both beginners with some programming experience or even those who know nothing about ML and SVM.
This course is for someone who is curious to learn the math behind SVM since this course contains an optional part for mathematics as well.
It is also for someone who wants to learn logistic regression from zero to hero; for someone who is an absolute beginner and has very little idea of machine learning.
Goals
What will you learn in this course:
- Learn the basics of machine learning
- Learn the basics of discriminative learning
- Learn the basics of linear discriminants
- Learn the basics of Support Vector Machine (SVM)
- Learn the basics of the sparsity of SVM and comparison with logistic regression
- Learn how to implement SVM on any dataset
- Learn the math behind SVM
Prerequisites
What are the prerequisites for this course?
- This course is designed for both beginners with some programming experience or even those who know nothing about ML and SVM.
Curriculum
Check out the detailed breakdown of what’s inside the course
Introduction to Course
4 Lectures
-
Introduction to Course
05:00
05:00
-
Why Machine Learning
10:21
10:21
-
Why Support Vector Machine
06:18
06:18
-
Course Overview
05:47
05:47
Introduction to Machine Learning
17 Lectures
Introduction to Python
16 Lectures
GridWorld Example
25 Lectures
Optional SVM Section
6 Lectures
Instructor Details
Packt Publishing
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