Classification using SVM classifier

 

Topics Covered:

1. Introduction to SVM
2. Importing required libraries
3. Reading Dataset
4. Distribution of classes
5. Selection of unwanted columns
6. Identifying Unwanted rows
7. Remove Unwanted columns
8. divide dataset Train/Test dataset
9. Modeling (SVM)
10. Results