Deep learning is a type of machine learning that learns by looking at lots of examples. In a way, deep learning is how we humans learn new things. For instance, you might teach a toddler to ...

As AI becomes more ubiquitous it is important to understand the distinctions between its various forms.

This guide provides a simple definition for deep learning that helps differentiate it from machine learning and AI along with eight practical examples of how deep learning is used today.

Machine-learning algorithms use statistics to find patterns in massive* amounts of data. And data, here, encompasses a lot of things—numbers, words, images, clicks, what have you.

Both deep learning and reinforcement learning are machine learning functions, which in turn are part of a wider set of artificial intelligence tools. What makes deep learning and reinforcement ...

Deep learning systems need a lot of data and a lot of time to work Next, let’s imagine that we want to teach a computer what a cat looks like using deep learning.

Deep learning itself isn’t that new, and researchers have been working on algorithms for many years, refining the approach and developing new algorithms. What has stimulated it recently is the ...

Machine learning uses algorithms to turn a data set into a model that can identify patterns or make predictions from new data. Which algorithm works best depends on the problem.

As machine-learning algorithms grow more sophisticated, artificial intelligence seems poised to revolutionize the practice of science itself.

Deep learning is a specific kind of ML, which leverages artificial neural networks – as opposed to algorithms – to glean patterns from complex or unstructured datasets.