and investment in their existing tools that now support machine learning development and deployment. Cloud-based ML-as-a-Service (MLaaS) In addition to the above approaches, most of the large ...

MLEM’s modular nature fits into any organization’s software development workflows based on Git and CI/CD, without engineers having to transition to a separate machine learning deployment and ...

Machine learning (ML), especially deep learning and ... Figure out what it would take to deploy an effective solution in its operational context, identify the real problems, then break proposed ...

WESTLAKE VILLAGE, Calif., May 12, 2020 – Eta Compute and Edge Impulse announce that they are partnering to accelerate the development and deployment of machine learning using Eta Compute’s ...

A multi-tier machine learning approach at the edge can help streamline both development and deployment for the artificial intelligence of things (AIoT). There are many challenges to implementing AI at ...

will further streamline AI research and deployment. Additionally, AI-enhanced automation tools will make Linux-based machine learning even more accessible to developers. In conclusion, Linux is the ...

The idea is that it streamlines training and deployment ... machine learning researchers,” the team explains. In other words, Apple has recognized the need to build open, easy-to-use development ...