Machine learning algorithms, such as neural networks and support vector machines, can handle the high-dimensional data typical in nanotechnology. These algorithms are capable of learning from data to make predictions or identify trends. For instance, they can predict how changes in the synthesis parameters of nanoparticles might affect their properties, thus saving time and resources in experimental setups.
