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Learn Support Vector Machines in R Studio. Basic SVM models to kernel-based advanced SVM models of Machine Learning

Setting up R Studio and R Crash Course

Installing R and R studio
Course Resources
Basics of R and R studio
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
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

Bonus Section

Bonus Lecture

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

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