Support Vector Machines

Lesson in the Machine Learning Roadmap · Stage 18: Classification

Last updated 14 September 2026

What is Support Vector Machines?

Support Vector Machines (SVMs) are a type of supervised learning algorithm used for classification and regression. They work by finding an optimal hyperplane that separates data points belonging to different classes with the largest possible margin. This hyperplane acts as a decision boundary, and new data points are classified based on which side of the hyperplane they fall on.

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Support Vector Machines: common questions

Can I learn Support Vector Machines in Hindi?

This lesson is written in English. Once you sign in, open it in the interactive course and ask the AI tutor to explain Support Vector Machines in Hindi or Hinglish. The tutor answers from this lesson’s own text, so it stays on the syllabus, and it runs on your own Google, OpenAI or Anthropic key.

Is this Support Vector Machines tutorial for beginners?

It is lesson 76 of 150 in the free Machine Learning roadmap, in stage 18, Classification. If you are new to Machine Learning, start from stage 1 and come back here in order; if you already know the earlier stages, this lesson stands on its own.