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SVM for Beginners: Support Vector Machines in R Studio

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

What does this course teach you?

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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