The Support Vector Machine (SVM) in Python Video

The Support Vector Machine (SVM) in Python Video

Objectives:

• Learn about Support Vector Machine (SVM) machines and their advantages and disadvantages.
• Perform regression analysis with the Support Vector Machine (SVM).
• When the Support Vector Machine (SVM) is used for regression, it is called Support Vector Regression (SVR).
• Explore the Support Vector Machine (SVM) classifier.
• Be able to explain the classification concepts of Hyper Plane, Boundary Line, Support Vector, and Kernel.
• Tune different parameters of SVMs using Python. The three different parameters are Kernel, Epsilon, and C-Penalty Co-efficient.
• Perform predictions after our SVM model is built.
• Evaluate a Support Vector Machine (SVM) model.

Instructor: Dhiraj Kumar

Length: 1 hour

Access period: For one year starting from purchase date