AWS Machine Learning Blog
Tag: MLOps
Accelerate machine learning time to value with Amazon SageMaker JumpStart and PwC’s MLOps accelerator
This is a guest blog post co-written with Vik Pant and Kyle Bassett from PwC. With organizations increasingly investing in machine learning (ML), ML adoption has become an integral part of business transformation strategies. A recent PwC CEO survey unveiled that 84% of Canadian CEOs agree that artificial intelligence (AI) will significantly change their business […]
Launch Amazon SageMaker Autopilot experiments directly from within Amazon SageMaker Pipelines to easily automate MLOps workflows
Amazon SageMaker Autopilot, a low-code machine learning (ML) service that automatically builds, trains, and tunes the best ML models based on tabular data, is now integrated with Amazon SageMaker Pipelines, the first purpose-built continuous integration and continuous delivery (CI/CD) service for ML. This enables the automation of an end-to-end flow of building ML models using […]
How Yara is using MLOps features of Amazon SageMaker to scale energy optimization across their ammonia plants
Learn how Yara is using Amazon SageMaker features, including the model registry, Amazon SageMaker Model Monitor, and Amazon SageMaker Pipelines to streamline the machine learning (ML) lifecycle by automating and standardizing MLOps practices. We provide an overview of the setup, showcasing the process of building, training, deploying, and monitoring ML models for plants around the globe.