To a large extent, supervised ML is for domains where automated machine learning does not perform well enough. Scientists add supervision to bring the performance up to an acceptable level.

Here are the differences between supervised, semi-supervised, and unsupervised learning -- and how each is valuable in the enterprise.

Artificial intelligence (AI) and machine learning (ML) are transforming our world. When it comes to these concepts there are important differences between supervised and unsupervised learning ...

Machine learning is performed in a manner that is either supervised, unsupervised, semi-supervised, or by reinforcement methods.

What does this all mean? The machine learns by processing massive amounts of data and in the process, AI learns to adapt to ever-changing real-world conditions.

Supervised learning just means the input data must be labeled or categorized for the algorithms to do their jobs. The system has to know what the input data is to figure out what to do with it.

Artificial Intelligence, Machine Learning & Deep Learning explained: AI vs ML vs DL discussed. Read about types of Machine Learning - Explanation & Dependencies.