We’ve gotten pretty good at building machine learning models. From legacy platforms like SAS to modern MPP databases and Hadoop clusters, if you want to train up regression or classification ...

From data collection, cleaning, and analysis - the amount of work required to prepare data for an machine learning model is very extensive Toggle navigation Subscribe ...

Zehra Cataltepe is the CEO of TAZI.AI an adaptive, explainable Machine Learning platform. She has more than 100 papers and patents on ML. While many believe that growth comes from acquiring new ...

The authors stress that AI deployment has surged ahead of efforts to instill ethical oversight. Technologies driven by ...

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.

We are writing history.” Daedalean CEO, Bas Gouverneur explains how the firm is certifying the first machine learning-enabled ...

Machine learning deployment platform OctoML raises $85M. Paul Sawers @psawers. November 1, 2021 9:04 AM ... which is a machine learning compiler framework for central processing units ...

ParallelM, a provider of machine learning operationalization (MLOps) software, has released a new version of MCenter that includes REST-based serving using Kubernetes to create a no-code, autoscaling ...

The OctoML team. (OctoML Photo) OctoML is charging ahead with its machine learning deployment software and on Friday announced a $15 million investment round to help support growth.. The Seattle ...

z System users with data behind their firewalls can now access IBM's training and deployment system for machine learning, packaged for convenience If you’re intrigued by IBM’s Watson AI as a ...