Reinforcement learning and unsupervised learning, the other categories of learning algorithms, have so far found very limited applications. Where does deep learning stand today?

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

Deep learning, a subset of machine learning, refers to machine learning that takes place on artificial intelligence neural networks.

What is supervised learning? One last thing you need to know: machine (and deep) learning comes in three flavors: supervised, unsupervised, and reinforcement.

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.

Supervised machine learning is a branch of AI. This article covers the relevant concepts, importance in various fields, practical use in investing, and CAPTCHA applications.

Deep learning algorithms, a subset of ML, have evolved to recognize faces with the same, if not better, accuracy as humans. However, it took until 2015 to build an algorithm that could recognize faces ...

Classification algorithms can find solutions to supervised learning problems that ask for a choice (or determination of probability) between two or more classes.

Semi-supervised learning: the best of both worlds When to use supervised vs unsupervised learning What is supervised learning? Combined with big data, this machine learning technique has the power to ...

Semi-supervised learning algorithms Semi-supervised learning goes back at least 15 years, possibly more; Jerry Zhu of the University of Wisconsin wrote a literature survey in 2005.