AWS News Blog
Category: Launch
New – Amazon SageMaker Pipelines Brings DevOps Capabilities to your Machine Learning Projects
Today, I’m extremely happy to announce Amazon SageMaker Pipelines, a new capability of Amazon SageMaker that makes it easy for data scientists and engineers to build, automate, and scale end to end machine learning pipelines. Machine learning (ML) is intrinsically experimental and unpredictable in nature. You spend days or weeks exploring and processing data in […]
Introducing Amazon SageMaker Data Wrangler, a Visual Interface to Prepare Data for Machine Learning
Today, I’m extremely happy to announce Amazon SageMaker Data Wrangler, a new capability of Amazon SageMaker that makes it faster for data scientists and engineers to prepare data for machine learning (ML) applications by using a visual interface. Whenever I ask a group of data scientists and ML engineers how much time they actually spend […]
New – Store, Discover, and Share Machine Learning Features with Amazon SageMaker Feature Store
Today, I’m extremely happy to announce Amazon SageMaker Feature Store, a new capability of Amazon SageMaker that makes it easy for data scientists and machine learning engineers to securely store, discover and share curated data used in training and prediction workflows. For all the importance of selecting the right algorithm to train machine learning (ML) […]
Amazon SageMaker Edge Manager Simplifies Operating Machine Learning Models on Edge Devices
Today, I’m extremely happy to announce Amazon SageMaker Edge Manager, a new capability of Amazon SageMaker that makes it easier to optimize, secure, monitor, and maintain machine learning models on a fleet of edge devices. Edge computing is certainly one of the most exciting developments in information technology. Indeed, thanks to continued advances in compute, […]
New – Amazon SageMaker Clarify Detects Bias and Increases the Transparency of Machine Learning Models
Today, I’m extremely happy to announce Amazon SageMaker Clarify, a new capability of Amazon SageMaker that helps customers detect bias in machine learning (ML) models, and increase transparency by helping explain model behavior to stakeholders and customers. As ML models are built by training algorithms that learn statistical patterns present in datasets, several questions immediately […]
In the Works – AWS Region in Melbourne, Australia
We launched new AWS Regions in Italy and South Africa in 2020, and are working on regions in Indonesia, Japan, Spain, India, and Switzerland. Melbourne, Australia in 2020 Today I am happy to announce that the Asia Pacific (Melbourne) region is in the works, and will open in the second half of 2022 with three […]
re:Invent 2020 Liveblog: Machine Learning Keynote
AWS Chief Evangelist Jeff Barr and Developer Advocates Martin Beeby and Steve Roberts liveblogged the first-ever Machine Learning Keynote. Swami Sivasubramanian, VP of Amazon Machine Learning shared the latest developments and launches in Amazon ML/AI, as well as demos of new technology, and insights from customers. Read the Machine Learning Keynote recap below. You can […]
Using Amazon CloudWatch Lambda Insights to Improve Operational Visibility
To balance costs, while at the same time ensuring the service levels needed to meet business requirements are met, some customers elect to continuously monitor and optimize their AWS Lambda functions. They collect and analyze metrics and logs to monitor performance, and to isolate errors for troubleshooting purposes. Additionally, they also seek to right-size function […]