Support Vector Machines in R (SVM in R)
Learn Support Vector Machines in R Studio. Basic SVM models to kernel-based advanced SVM models of Machine Learning
Updated on Sep, 2023
Language - English
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.
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.
Who this course is for:
- People pursuing a career in data science
- Working Professionals beginning their Data journey
- Statisticians needing more practical experience
- Anyone curious to master SVM technique from Beginner to Advanced in short span of time
Goals
What will you learn in this course:
- 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
Prerequisites
What are the prerequisites for this course?
- Students will need to install R and R Studio software but we have a separate lecture to help you install the same
Curriculum
Check out the detailed breakdown of what’s inside the course
Setting up R Studio
9 Lectures
-
Installing R and R studio
05:52
05:52
-
Course Resources
-
Basics of R and R studio
10:47
10:47
-
Packages in R
10:52
10:52
-
Inputting data part 1: Inbuilt datasets of R
04:21
04:21
-
Inputting data part 2: Manual data entry
03:11
03:11
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Inputting data part 3: Importing from CSV or Text files
06:49
06:49
-
Creating Barplots in R
13:42
13:42
-
Creating Histograms in R
06:01
06:01
Machine Learning Basics
2 Lectures
Maximum Margin Classifier
4 Lectures
Support Vector Classifier
2 Lectures
Support Vector Machines
1 Lectures
Creating Support Vector Machine Model in R
9 Lectures
Instructor Details
Abhishek and Pukhraj
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.
Founded by Abhishek Bansal and Pukhraj Parikh.
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.
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