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.

The designation recognizes Alteryx for providing business analysts, data scientists and ML practitioners with automated, cutting-edge tools to create and deploy predictive models on AWS.

The new tools and capabilities will make it faster and cheaper to label data, train machine learning models, and deploy models for inference.

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

In contrast, deploying those models is a face-meltingly painful experience. This despite the fact that machine learning models are primarily only useful to a business insofar as they’re deployed ...

Amazon's SageMaker for machine learning got a series of upgrades today including AutoML and services to help with experiments, debugging, and notebooks.

They introduced the Inferentia chip in 2019 to help speed up inference learning. Then last year the company launched a second Trainium chip, designed specifically for machine learning models.

MLflow is a popular open-source platform for the machine learning lifecycle, including experimentation, reproducibility, deployment and monitoring of machine learning models.

At re:Invent 2022, the cloud services provider updated its managed machine learning service to include new notebook and governance features.

Amazon said the AWS AI & ML Scholarship will provide no-cost access to dozens of hours of free machine learning model training and educational materials.