Machine learning has many subcategories and techniques, each with some similarities and differences. It is critical to understand how these algorithms differ in order to make better decisions when dealing with classification or regression problems. One of the most significant distinctions is between supervised and unsupervised learning, technique, application, limitations, and data.
