<ul><li>Support Vector Machine (SVM) is a supervised machine learning algorithm used mainly for classification, but it can also be used for regression.</li><li>SVM finds the best boundary (hyperplane) that separates different classes in the dataset, maximizing the margin between the boundary and the nearest points from each class.</li><li>SVM uses the kernel trick to operate in a higher-dimensional space without manually transforming the data.</li><li>SVM can be used for regression tasks, known as Support Vector Regression (SVR).</li></ul>

Support Vector Machine (SVM) Explained Simply — With Python Code

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