Nanotechnology often deals with complex datasets originating from various experiments and simulations. These datasets can be high-dimensional and non-linear, making traditional analysis methods less effective. SVMs, with their ability to handle such complexities, offer a powerful tool for data analysis in nanotechnology. They can be used for tasks such as material property prediction, image classification of nanostructures, and even in the development of nano-drug delivery systems.
