Non Linear SVM Classification -using SCKIT learn
Overview
Syllabus
- Project Overview
- In this 1-hour long project-based course, you will learn 'Support Vector Machines' model in Machine Learning ,we will focus to perform Non linear SVM Classification. [Add features to make a dataset linearly separable,Build linear SVM Classifier using Polynomial features, Build SVM classifiers with a polynomial kernel,Illustrate similarity feature using Gaussian RBF,Build SVM Classifiers using an RBF kernel( Python Code and scientific libraries)]
This project gives you easy access to the invaluable learning techniques used by experts
This project favors a hands on approach, growing an intuitive understanding of machine learning through concrete working examples and just a little bit of theory .
I highly recommend your experiment with the code examples in parallel as discussed in the lecture
Taught by
Dr. Ashish Dikshit, PHD
