Support Vector Machines for Classification: Machine Learning

Learn to apply Support Vector Machines for Classification from a Data Science expert. Code templates included.

4.50 (7 reviews)
Udemy
platform
English
language
Data Science
category
instructor
1,628
students
2 hours
content
Jan 2024
last update
$19.99
regular price

What you will learn

Master Support Vector Machines for Classification in Python

Become an advanced, confident, and modern data scientist from scratch

Become job-ready by understanding how Support Vector Machines really work behind the scenes

Apply robust Data Science techniques for Support Vector Machines

How to think and work like a data scientist: problem-solving, researching, workflows

Get fast and friendly support in the Q&A area

Description

You’ve just stumbled upon the most complete, in-depth Support Vector Machines for Classification course online.

Whether you want to:

- build the skills you need to get your first data science job

- move to a more senior software developer position

- become a computer scientist mastering in data science

- or just learn SVM to be able to create your own projects quickly.

...this complete Support Vector Machines for Classification Masterclass is the course you need to do all of this, and more.


This course is designed to give you the Support Vector Machine skills you need to become a data science expert. By the end of the course, you will understand the SVM method extremely well and be able to apply it in your own data science projects and be productive as a computer scientist and developer.


What makes this course a bestseller?

Like you, thousands of others were frustrated and fed up with fragmented Youtube tutorials or incomplete or outdated courses which assume you already know a bunch of stuff, as well as thick, college-like textbooks able to send even the most caffeine-fuelled coder to sleep.

Like you, they were tired of low-quality lessons, poorly explained topics, and confusing info presented in the wrong way. That’s why so many find success in this complete Support Vector Machines for Classification course. It’s designed with simplicity and seamless progression in mind through its content.

This course assumes no previous data science experience and takes you from absolute beginner core concepts. You will learn the core dimensionality reduction skills and master the SVM technique. It's a one-stop shop to learn SVM. If you want to go beyond the core content you can do so at any time.


What if I have questions?

As if this course wasn’t complete enough, I offer full support, answering any questions you have.

This means you’ll never find yourself stuck on one lesson for days on end. With my hand-holding guidance, you’ll progress smoothly through this course without any major roadblocks.


Moreover, the course is packed with practical exercises that are based on real-life case studies. So not only will you learn the theory, but you will also get lots of hands-on practice building your own models.

And as a bonus, this course includes Python code templates which you can download and use on your own projects.


Ready to get started, developer?

Enroll now using the “Add to Cart” button on the right, and get started on your way to creative, advanced SVM brilliance. Or, take this course for a free spin using the preview feature, so you know you’re 100% certain this course is for you.

See you on the inside (hurry, Support Vector Machines are waiting!)

Content

Code Environment Setup

Google Colab for Programming in Python

Support Vector Machines - Data Science Project

Introduction to the Dataset
Partition of the Dataset
Transformation to Data Matrix
Dimensionality Reduction
Support Vector Machine - Linear Kernel
Support Vector Machines - Polynomial Kernels
Support Vector Machine - Radial Basis Function (RBF) Kernel

Screenshots

Support Vector Machines for Classification: Machine Learning - Screenshot_01Support Vector Machines for Classification: Machine Learning - Screenshot_02Support Vector Machines for Classification: Machine Learning - Screenshot_03Support Vector Machines for Classification: Machine Learning - Screenshot_04

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Enrollment distribution

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5109086
udemy ID
1/24/2023
course created date
1/28/2023
course indexed date
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