Support Vector Machine Classification in Python
In this 1-hour long guided project-based course, you will learn how to use Python to implement a Support Vector Machine algorithm for classification. This type of algorithm classifies output data and makes predictions. The output of this model is a set of visualized scattered plots separated with a straight line. You will learn the fundamental theory and practical illustrations behind Support Vector Machines and learn to fit, examine, and utilize supervised Classification models using SVM to classify data, using Python. We will walk you step-by-step into Machine Learning supervised problems. With every task in this project, you will expand your knowledge, develop new skills, and broaden your experience in Machine Learning. Particularly, you will build a Support Vector Machine algorithm, and by the end of this project, you will be able to build your own SVM classification model with amazing visualization. In order to be successful in this project, you should just know the basics of Python and classification algorithms.
Support Vector Machine (SVM)
由 DO 提供2020年11月29日
This project is very much educative from start to finish and it enables a beginner to master some key concepts.
由 DA 提供2020年8月18日
Gave me a good intuition for applying SVM classifier in python as well as visualising predictions, thanks for
guiding me through this.
由 MA 提供2020年9月11日
Good Course. But voice of instructor was not clear enough and he was very slow. Overall, I have learned some new things. Thanks Instructor.
由 NK 提供2020年5月5日
Nice experience to get acquinted with the algorithm