How Does Unsupervised Learning Work? In unsupervised learning, the key characteristic is that the data provided to the algorithm comes without any pre-existing labels or predefined categories.

We’ve previously covered algorithms and artificial neural networks – concepts surrounding deep learning – but this time we’ll take a look at how deep learning systems actually learn.

Unsupervised learning algorithms learn from unlabeled data, where the desired output is not known. These algorithms aim to discover hidden patterns or structures in the data.

Unsupervised learning is a type of machine learning algorithm that is becoming more popular as the amount of data being produced continues to increase.

Supervised and unsupervised learning describe two ways in which machines - algorithms - can be set loose on a data set and expected to learn something useful from it. Today, supervised machine ...

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

With unsupervised learning, machine learning and AI-based algorithms are constantly working to discover new potential ways that they could possibly be attacked in the future.

Cortica says unsupervised machine learning will allow autonomous cars of the future to better adapt to new situations on the road.