Support Vector Machine Classification in Python
6051 ya inscrito
6051 ya inscrito
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)
En un video que se reproduce en una pantalla dividida con tu área de trabajo, tu instructor te guiará en cada paso:
Tu espacio de trabajo es un escritorio virtual directamente en tu navegador, no requiere descarga.
En un video de pantalla dividida, tu instructor te guía paso a paso
por DA18 de ago. de 2020
Gave me a good intuition for applying SVM classifier in python as well as visualising predictions, thanks for
guiding me through this.
por RR7 de jun. de 2020
I really enjoyed working with this project. Thank you so much for the valuable teaching.
por NK5 de may. de 2020
Nice experience to get acquinted with the algorithm
por AM2 de may. de 2020
Straight to the point, take a little bit of time and it is very useful for anyone seeking more knowledge in this domain.
Thumbs up to the instructor.