Support Vector Machine Classification in Python

In this 1-hour long guided project-based course, you will delve into the world of Support Vector Machine (SVM) classification in Python. Through a hands-on approach, you will uncover the fundamental theory and practical illustrations behind SVM, equipping you with the skills to build, examine, and utilize supervised classification models using Python. Whether you are a beginner or have some experience in Python and classification algorithms, this course will expand your knowledge and expertise in Machine Learning.

• Import the dataset and perform training/testing set splits
• Apply feature scaling for normalization
• Build an SVM classifier and make predictions
• Construct a Confusion Matrix and visualize the results

By the end of this project, you will have the capability to construct your own SVM classification model with remarkable visualization. This course is a stepping stone for those looking to advance their skills in Machine Learning, providing a solid foundation for understanding and implementing SVM algorithms in Python.