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.

AutoML: Democratizing machine learning. Lately, a new buzzword, “AutoML,” has started to appear to denote that a machine learning algorithm comes with an additional meta-layer of automation.

A machine learning algorithm, on the other hand, might recognize that the strongest signal differentiating a dog from a cat is whether the photo is a bright outdoor photo or a dim indoor photo.

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.

Machine learning is a subfield of artificial intelligence (AI) that involves the development of algorithms and statistical models, which allow computers to learn from data without being explicitly ...

The learning curve for implementing machine learning solutions is generally steep, so you’ll need a solid understanding of statistics, data science, and algorithm development.

Chinese cloud vendor releases "core codes" of its Alink platform on GitHub, uploading a range of algorithm libraries that support processes for machine learning tasks, such as online product ...

Deep learning defined. Deep learning is a form of machine learning that models patterns in data as complex, multi-layered networks. Because deep learning is the most general way to model a problem ...

SAVANA uses a machine learning algorithm to identify cancer-specific structural variations and copy number aberrations in long-read DNA sequencing data. The complex structure of cancer genomes ...