SVM for Beginners: Support Vector Machines in R Studio

BY
Udemy

Lavel

Beginner

Mode

Online

Fees

₹ 449 2899

Quick Facts

particular details
Medium of instructions English
Mode of learning Self study
Mode of Delivery Video and Text Based

Course and certificate fees

Fees information
₹ 449  ₹2,899
certificate availability

Yes

certificate providing authority

Udemy

The syllabus

Setting up R Studio and R Crash Course

  • Installing R and R Studio
  • Course Resources
  • Basics of R and R Studio
  • This is a milestone!
  • Packages in R
  • Inputting data part 1: Inbuilt datasets of R
  • Inputting data part 2: Manual data entry
  • Inputting data part 3: Importing from CSV or Text files
  • Creating Barplots in R
  • Creating Histograms in R

Machine Learning Basics

  • Introduction to Machine Learning
  • Building a Machine Learning Model

Maximum Margin Classifier

  • Course flow
  • The Concept of a Hyperplane
  • Maximum Margin Classifier
  • Limitations of Maximum Margin Classifier

Support Vector Classifier

  • Support Vector classifiers
  • Limitations of Support Vector Classifiers
  • Quiz

Support Vector Machines

  • Kernel Based Support Vector Machines
  • Quiz

Creating Support Vector Machine Model in R

  • The Data set for the Classification problem
  • Importing Data into R
  • Test-Train Split
  • More about test-train split
  • Classification SVM model using Linear Kernel
  • Hyperparameter Tuning for Linear Kernel
  • Polynomial Kernel with Hyperparameter Tuning
  • Radial Kernel with Hyperparameter Tuning
  • Quiz
  • The Data set for the Regression problem
  • SVM based Regression Model in R

Appendix 1: Preprocessing and Preparing Data before making any model

  • Gathering Business Knowledge
  • Data Exploration
  • The Data and the Data Dictionary
  • Importing the dataset into R
  • Univariate Analysis and EDD
  • EDD in R
  • Outlier Treatment
  • Outlier Treatment in R
  • Missing Value imputation
  • Missing Value imputation in R
  • Seasonality in Data
  • Bi-variate Analysis and Variable Transformation
  • Variable transformation in R
  • Non Usable Variables
  • Dummy variable creation: Handling qualitative data
  • Dummy variable creation in R
  • Correlation Matrix and cause-effect relationship
  • Correlation Matrix in R
  • Quiz

Bonus Section

  • The final milestone!
  • Bonus Lecture

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