A very quick note on machine learning Before we dive into supervised and unsupervised learning, let’s have a zoomed-out overview of what machine learning is.

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.

But machine learning comes in many different flavors. In this post, we will explore supervised and unsupervised learning, the two main categories of machine learning algorithms.

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

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 machine learning Semi-supervised machine learning strikes a balance between its supervised and unsupervised counterparts, leveraging the best of both worlds.

Machine-learning and, in particular, deep-learning approaches can help process and analyze large volumes of data. In supervised deep learning, convolutional neural networks learn from training ...

Professor Li Hang's new book is positioned as a university textbook and a reference for professionals, suitable for readers with a certain background in calculus, linear algebra, and computer science.

AI has classically come in three forms, supervised learning, unsupervised learning, and reinforcement learning.