Similarly, a learning algorithm could be left alone to create its own rules that will apply when it is provided with a large set of the object–like a group of apples, and the machine figures out ...

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.

Meta-learning is an algorithm that essentially learns how to learn. It can also learn with less. Meaning, if you have a limited quantity of data, meta-learning can be valuable.

Learn how Google uses machine learning models and algorithms in search. When it comes to machine learning, there are some broad concepts and terms that everyone in search should know.

Proximal algorithms are useful for obtaining solutions to difficult optimization problems, especially those involving nonsmooth or composite objective functions. A proximal algorithm is one whose ...

Machine learning is hard. Algorithms in a particular use case often either don't work or don't work well enough, leading to some serious debugging. And finding the perfect algorithm–the set of ...

20 Gianfrancesco MA, Tamang S, Yazdany J, Schmajuk G. Potential biases in machine learning algorithms using electronic health record data. JAMA Intern Med. 2018;178 (11):1544–7.

Systems controlled by next-generation computing algorithms could give rise to better and more efficient machine learning products, a new study suggests.

Machine learning is an area of artificial intelligence (AI) with a concept that a computer program can learn and adapt to new data without human intervention. A complex algorithm or source code is ...

The development of deep learning and artificial intelligence (AI) could also mean that companies are unaware of how or why a machine comes to a particular conclusion, he noted.