Machine learning may help manage and organize enterprise systems -- with their "highly complex interactions between systems and components, complex data access patterns and relationships." ...

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 new study published in the journal Cell Systems on November 20, 2019, reports the use of machine learning to help form complex cell architectures from pluripotent stem cells, a sophisticated ...

The book will also show you how to develop accurate models by automating time-consuming and repetitive tasks in the machine learning development lifecycle. By the end of this machine learning book, ...

This GitHub repository contains the implementation of a project that aims to locate damaged areas after an earthquake using satellite images, a Building Damage Assessment Machine Learning Model, ...

Machine learning algorithms. Machine learning depends on a number of algorithms for turning a data set into a model. Which algorithm works best depends on the kind of problem you’re solving, the ...

Machine learning applications in data centers (or “the cloud”) have pervasively changed our environment. Advances in speech recognition and natural language understanding have enabled personal ...

Quantity and quality of data are not enough to take full advantage of machine learning. The structures built around data -- and the way data is structured -- influence the value you can derive ...

TensorFlow 2.0, released in October 2019, revamped the framework significantly based on user feedback. The result is a machine learning framework that is easier to work with—for example, by ...