Training machine learning models for computer vision use cases takes massive amounts of images. Often, those images are mislabeled, broken or duplicated, leading to sub-par model performance. But with ...

SAN FRANCISCO--(BUSINESS WIRE)--Iterative, the MLOps company dedicated to streamlining the workflow of data scientists and machine learning (ML) engineers, today announced a free extension to Visual ...

Treating annotation as a data understanding problem, rather than a labeling workflow challenge, can systematically drive down error rates and reduce the time and cost of producing high-quality data ...

Researchers have developed a powerful new software toolbox that allows realistic brain models to be trained directly on data.

Microsoft updated its machine learning dev tooling with ML.NET 2.0 and a new version of Model Builder. ML.NET is the company's open source, cross-platform machine learning framework for .NET ...

Machine learning has a wide range of applications in the finance, healthcare, marketing and transportation industries. It is used to analyze and process large amounts of data, make predictions, and ...

University of Alberta researchers have trained a machine learning model to identify people with post-traumatic stress disorder with 80 per cent accuracy by analyzing text data. The model could one day ...