The company said it’s addressing common pain points in the deployment of machine learning, a branch of artificial ... Exposing the inferencing engine as an API makes it possible for developers ...

--(BUSINESS WIRE)--ParallelM, the leader in MLOps, today released a new version of MCenter that includes REST-based ... addresses the deployment challenges of machine learning for real-time ...

With this release, data scientists can quickly create robust autoscaling REST services for their machine learning models to better serve real-time applications in the cloud or on-premise. The 1.3 ...

According to Ashley Kramer, Alteryx's VP of Product Management, Promote will address this gap by allowing deployment ... Microsoft's Azure Machine Learning generates a REST-based Web service ...

The problem is 47 percent of fully trained ML models never reach production, and the rest take an average ... OctoML is a machine learning deployment platform with a mission to make machine ...

We called it Machine Learning October Fest ... Besides being able to deploy ML models on Spark and Delta, MLFlow can also export them as REST services to be run on any platform, or on Kubernetes ...

IBM is pushing it as a pipeline for building, managing, and running machine learning models through visual tools for each step of the process and RESTful APIs for deployment and management.

Available on the GPT store, Monster API’s Agent gives all developers an easy and fast process to fine tune and deploy more ... frameworks for machine learning but also navigating ...

The Amazon Machine Learning service offers an easy way to do ... AML works with data stored in Amazon S3, Redshift, or RDS, and provides an API set for creating, connecting with, and manipulating ...

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 ...