Course description

You're looking for a complete Support Vector Machines course that teaches you everything you need to create a SVM model in R, right?

You've found the right Support Vector Machines techniques course!

How this course will help you?

A Verifiable Certificate of Completion is presented to all students who undertake this Machine learning advanced course.

If you are a business manager or an executive, or a student who wants to learn and apply machine learning in Real world problems of business, this course will give you a solid base for that by teaching you some of the advanced technique of machine learning, which are Support Vector Machines.

Why should you choose this course?

This course covers all the steps that one should take while solving a business problem through SVM.

Most courses only focus on teaching how to run the analysis but we believe that what happens before and after running analysis is even more important i.e. before running analysis it is very important that you have the right data and do some pre-processing on it. And after running analysis, you should be able to judge how good your model is and interpret the results to actually be able to help your business.

What makes us qualified to teach you?

The course is taught by Abhishek and Pukhraj. As managers in Global Analytics Consulting firm, we have helped businesses solve their business problem using machine learning techniques and we have used our experience to include the practical aspects of data analysis in this course

We are also the creators of some of the most popular online courses - with over 150,000 enrollments and thousands of 5-star reviews like these ones:

This is very good, i love the fact the all explanation given can be understood by a layman - Joshua

Thank you Author for this wonderful course. You are the best and this course is worth any price. - Daisy

Our Promise

Teaching our students is our job and we are committed to it. If you have any questions about the course content, practice sheet or anything related to any topic, you can always post a question in the course or send us a direct message.

Download Practice files, take Quizzes, and complete Assignments

With each lecture, there are class notes attached for you to follow along. You can also take quizzes to check your understanding of concepts. Each section contains a practice assignment for you to practically implement your learning.

Go ahead and click the enroll button, and I'll see you in lesson 1!

Cheers

Start-Tech Academy

 

Requirements:

  • Students will need to install R and R Studio software but we have a separate lecture to help you install the same


What you'll learn:

  • Get a solid understanding of Support Vector Machines (SVM)
  • Understand the business scenarios where Support Vector Machines (SVM) is applicable
  • Tune a machine learning model's hyperparameters and evaluate its performance.
  • Use Support Vector Machines (SVM) to make predictions
  • Implementation of SVM models in R programming language - R Studio

Course curriculum

  • 1
    Setting up R Studio and R Crash Course
    • 001 Installing R and R studio FREE PREVIEW
    • 002 Basics of R and R studio
    • 003 Packages in R
    • 004 Inputting data part 1 Inbuilt datasets of R
    • Course Resources
    • 005 Inputting data part 2 Manual data entry
    • 006 Inputting data part 3 Importing from CSV or Text files
    • 007 Creating Barplots in R
    • 008 Creating Histograms in R
  • 2
    Machine Learning Basics
    • 009 Introduction to Machine Learning
    • 010 Building a Machine Learning Model
  • 3
    Maximum Margin Classifier
    • 011 Course flow
    • 012 The Concept of a Hyperplane
    • 013 Maximum Margin Classifier
    • 014 Limitations of Maximum Margin Classifier
  • 4
    Support Vector Classifier
    • 015 Support Vector classifiers
    • 016 Limitations of Support Vector Classifiers
  • 5
    Support Vector Machines
    • 017 Kernel Based Support Vector Machines
  • 6
    Creating Support Vector Machine Model in R
    • 018 The Data set for the Classification problem
    • 019 Importing Data into R
    • 020 Test-Train Split
    • 021 Classification SVM model using Linear Kernel
    • 022 Hyperparameter Tuning for Linear Kernel
    • 023 Polynomial Kernel with Hyperparameter Tuning
    • 024 Radial Kernel with Hyperparameter Tuning
    • 025 The Data set for the Regression problem
    • 026 SVM based Regression Model in R

Meet your instructor!

Start-Tech Academy
A technology-based analytics education company


Founded by Abhishek Bansal and Pukhraj Parikh, Start-Tech Academy is a technology-based analytics education company and aims at bringing together the analytics companies and interested Learners. 

Our top quality training content along with internships and project opportunities helps students in launching their Analytics journey. 

Working as a Project manager in an Analytics consulting firm, Pukhraj has multiple years of experience working on analytics tools and software. He is competent in  MS office suites, Cloud computing, SQL, Tableau, SAS, Google analytics and Python.

Abhishek worked as an Acquisition Process owner in a leading telecom company before moving on to learning and teaching technologies like Machine Learning and Artificial Intelligence.

Take this course today!

"Machine Learning: Support Vector Machines in R (SVM in R)"

Bundle including this course!