I believe an approach to machine learning deployment that’s based on an industry standard, language-agnostic, and able to represent a broad range of algorithms is the clear path forward.

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

Accelerate the process of machine learning model development, evaluation, and deployment Help improve overall performance, accuracy, and efficiency of machine learning models ...

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 ...

Designed to support the entire machine learning lifecycle -- from data ingestion and model training to deployment and monitoring -- Azure ML is empowering developers to integrate predictive ...

Iterative has launched Machine Learning Engineering Management an open source model deployment and registry tool.

Gynecological cancers, including breast, ovarian, and cervical malignancies, account for a significant global health burden among women. The review outlines how a spectrum of machine learning (ML) ...