Meanwhile, everything you build and output is based upon the popular Tensorflow standard–what’s known as a machine learning framework–and applicable to apps on the web, iOS, and Android.

Since rolling out Cloud Machine Learning earlier this year, Google has built up its enterprise offerings to make it a compelling reason to move to the Google Cloud Platform.

Data analytics developer Databricks Inc. today announced the general availability of Databricks Model Serving, a serverless real-time inferencing service that deploys real-time machine learning ...

Cloudera has launched Applied ML Prototypes, complete machine learning projects for use cases that give data scientists a running start on development.

A brief introduction to Spark MLlib's APIs for basic statistics, classification, clustering, and collaborative filtering, and what they can do for you ...

Microsoft has released the 0.6 version of its ML.Net machine learning framework, aimed at .Net developers. The update adds a new and more useful model-building API set, the ability to use more ...

In 2016, Google LLC released a sort of digital Pictionary called Quick, Draw!, a machine learning tool that let people doodle sketches, which would then be analyzed by the tool. Apparently it ...

MOUNTAIN VIEW, CALIF.—Google is launching a new SDK for machine learning for its Firebase developer platform called "ML Kit." The new SDK offers ready-to-use APIs for some of the most common ...

Like the rest of the tech world, Apple wants to make AI on your mobile device as fast and powerful as possible. That’s why the company unveiled a new machine learning framework API for ...