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

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


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

Overview

About this Course
You're looking for a complete Support Vector Machines course that teaches you everything you need to create a Support Vector Machines model in Python, 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 Decision tree.

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.

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

Cheers

Start-Tech Academy

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

Course Information

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

What you will learn
Get a solid understanding of Support Vector Machines
Understand the business scenarios where Support Vector Machines is applicable
Tune a machine learning model's hyperparameters and evaluate its performance.
Use Support Vector Machines to make predictions

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

• Lifetime Access to Each Course
• Certificate on Completion of Course
• No Extra Charges Or Admin Fees
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• High Priority Support After Sales.
• Big Discounts on Individual Courses

Course Specifications

Our great AI and Machine Learning courses include Artificial Intelligence, Coding and Programming. 

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Adult education is the non-credential activity of gaining skills and improved education. 

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Online education is electronically supported learning that relies on the Internet for teacher/student interaction. 

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A short course is a learning programme that gives you combined content or specific skills training in a short period of time. Short courses often lean towards the more practical side of things and have less theory than a university course – this gives you a more hands-on experience within your field of interest.

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Course duration is 24 hours.

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