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.

A team from Google Research has open-sourced Model Search, an automated machine learning (AutoML) platform for designing deep-learning models. Experimental results show that the system produces models ...

For instance, machine-learning developers might focus on having features that are compatible with the model and predictive, meaning they are expected to improve the model's performance.

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 ...

This article breaks down the machine learning problem known as Learning to Rank and can teach you how to build your own web ranking algorithm. Frédéric Dubut March 13, 2019 ...

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