Machine learning adoption continues to grow rapidly across industries. Here are the major trends Gartner believes will shape its future use.
A machine learning model could more accurately predict the ocean currents, which could help in plastic pollution and oil spill clean-ups.
Researchers from Heriot-Watt University and EPFL have developed a machine learning algorithm to more accurately forecast amine emissions.
Reaping Business and Operational Benefits by Moving Analytics and Machine Learning to Hybrid Cloud Chapter 1: Why Hybrid Cloud and Why Now? Hybrid cloud lets businesses deploy workloads and data on a mix of on-premises, private cloud, or public cloud infrastructure. That gives businesses great flexibility and allows them to optimize workloads by selectively matching […]
Advances in both computational modeling and machine learning have shown the promise of a clear paradigm shift in personalized medicine. As such, a new research effort seeks to leverage machine learning to create new ways to identify and track heart disease localization and progression.
The future of recommender systems is real-time machine learning. Here's everything you need to know about what that means for enterprise applications.
Analytics and ML performance and speed to results can be vastly improved when using a hybrid cloud that incorporates a modern database.
The Vertica SQL database and in-database machine learning solutions support the entire predictive analytics process with massively parallel processing and a familiar SQL interface.
Machine learning is being deployed by organizations in finance and retail to prevent fraud, but the deployment of ML is not an instant fix.
A hybrid cloud approach lets businesses essentially pick and choose the various aspects of their analytics and ML workloads that they want to keep on-premises and which they want to run in the cloud.