Can you explain Support Vector Machines?
An example of an AI chatbot conversation about Support Vector Machines in machine learning.
Can you explain Support Vector Machines?
Sure! Support Vector Machines (SVM) are supervised learning models used for classification and regression tasks.
How do SVMs work?
SVMs work by finding the hyperplane that best separates the data points of different classes in a high-dimensional space.
What are the advantages of using SVMs?
Some advantages include their effectiveness in high-dimensional spaces and their ability to model non-linear decision boundaries using kernel functions.
Can you give me an example of SVM in action?
Certainly! For instance, SVMs can be used in image classification to distinguish between different types of objects in pictures.
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