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.

Alteryx Promote delivers AI/machine learning model deployment, ... Microsoft's SQL Server 2016 allows for R-based machine learning models to be stored in its databases and R code that uses the ...

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 ...

The company decided to make this a standard and to open source it to try and move machine learning model deployment forward. “Graphpipe sits on that intersection between solving a business ...

Iterative has launched Machine Learning Engineering Management an open source model deployment and registry tool. MLOps Company Iterative Introduces the First Open, Git-based Machine Learning ...

The 10 hottest data science and machine learning tools include MLflow 3.0, PyTorch, Snowflake Data Science Agent and ...

TrueFoundry helps users turn ML models built on tools such as Jupyter Notebooks into live APIs, making it easier to build, track, and deploy models without deep knowledge of systems like Kubernetes.

ParallelM Solves Real-World Machine-Learning Deployment Challenge with Kubernetes Autoscaling REST Endpoint. Low-latency model serving at scale helps data scientists deliver models into production ...

MLOps platform Iterative, which announced a $20 million Series A round almost exactly a year ago, today launched MLEM, an open source Git-based machine learning model management and deployment tool.

“Machine learning is a method of analyzing data using an analytical model that is built automatically, or ‘learned’, from training data,” said Rick Negrin, who is the VP of Product ...