While building machine learning models is fundamental to today’s narrow applications of AI, there are a variety of different ways to go about realizing the same ends.

Machine learning models are mathematical representations of real-world processes that are used to make predictions, and are created by providing training data for an algorithm to learn from.

Today’s data scientists and machine learning engineers now have a wide range of choices for how they build models to address the various patterns of AI for their particular needs.

Machine learning is an integral part of high-stakes decision-making in a broad swath of human-computer interactions. You ...

Machine learning and traditional algorithms are “two substantially different ways of computing, and algorithms with predictions is a way to bridge the two,” said Piotr Indyk, a computer scientist at ...

Researchers have created a taxonomy and outlined steps that developers can take to design features in machine-learning models that are easier for decision-makers to understand.

New machine learning algorithm promises advances in computing Digital twin models may enhance future autonomous systems Date: May 9, 2024 Source: Ohio State University ...

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