Data Science, Data Analysis, Machine Learning, Statistics, Data Visualization.
well when the data is linearly separable, meaning you can draw a straight line (or hyperplane in higher dimensions) to separate different classes. -High-Dimensional Spaces: SVMs are particularly useful in high-dimensional spaces. For example, in image classification tasks where each pixel can be