Today, machine learning is quickly gaining traction with developers, and AWS wants to help remove some of the obstacles associated with building and deploying machine learning models.

AWS says it can speed up training by up to 50%. Next, Amazon SageMaker Inference Recommender automates load testing and optimizes model performance across machine learning instances.

At its annual re:Invent conference, AWS today rolled out a slew of new features for SageMaker, the company’s managed service for building, training and deploying machine learning (ML) models ...

After just four months, customers are building more than one million models per month. H2O.ai announced that it has added key new features to Driverless AI based on customer insights and usage.

Amazon Web Services, Inc. (AWS), an Amazon.com, Inc. company, is releasing Amazon Elastic Compute Cloud (Amazon EC2) DL1 instances, a new instance type designed for training machine learning models.

The interface gives developers a place where they can prototype, build, train, and deploy machine learning models for cloud and mobile apps.

Driverless AI, currently in beta, is billed by H2O.ai as an “expert system for AI” — a way to automate the kinds of expertise that data scientists bring to developing machine learning models.