Learn how to build an Android app that can automatically process an image using on-device and in-the-cloud machine learning. ML Kit image labeling feature is probably one of the more important ...

Being meticulous about the data labeling process is important for improving the quality of data, which has a direct impact on the quality of the predictions made by the machine learning models. It can ...

DataRobot is acquiring Paxata to add data prep to machine learning platform The company’s products are based on research that began at the Stanford AI Lab in 2015.

Datasaur, a member of the Y Combinator Winter 2020 batch, announced a $3.9 million investment today to help solve that problem with a platform designed for machine learning labeling teams. The […] ...

Today, 10 million people interact with hCaptcha every month on thousands of websites, powering dozens to hundreds of machine learning-labeling projects at a time. Subscribe to the Design newsletter.

The future of data labeling in machine learning. The progression of AI and ML is not looking to slow down anytime soon. Alongside this is the increased need for high-quality labeled datasets.

SAN FRANCISCO, Dec. 3, 2018 /PRNewswire/ -- Ouster, a leading manufacturer of high-resolution lidar sensors, today announced a partnership with leading data labeling companies Playment and Scale ...

SINGAPORE, SINGAPORE / ACCESSWIRE / June 22, 2020 / Bytebride, an automated provider for services to collect, manage, and process data sets for machine learning applications, was recently ...

Scientists demonstrate machine learning tool to efficiently process complex solar data Iterative labeling technique can be applied, adapted to other big data challenges ...

It also announced a new tool called Application Studio that provides a way to build common machine learning applications using templates and predefined components. Snorkel AI scores $35M Series B ...