AWS News Blog

Category: AWS re:Invent

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 […]

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New – Profile Your Machine Learning Training Jobs With Amazon SageMaker Debugger

Today, I’m extremely happy to announce that Amazon SageMaker Debugger can now profile machine learning models, making it much easier to identify and fix training issues caused by hardware resource usage. Despite its impressive performance on a wide range of business problems, machine learning (ML) remains a bit of a mysterious topic. Getting things right […]

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New – Data Parallelism Library in Amazon SageMaker Simplifies Training on Large Datasets

Today, I’m particularly happy to announce that Amazon SageMaker now supports a new data parallelism library that makes it easier to train models on datasets that may be as large as hundreds or thousands of gigabytes. As data sets and models grow larger and more sophisticated, machine learning (ML) practitioners working on large distributed training […]

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Amazon SageMaker Simplifies Training Deep Learning Models With Billions of Parameters

Today, I’m extremely happy to announce that Amazon SageMaker simplifies the training of very large deep learning models that were previously difficult to train due to hardware limitations. In the last 10 years, a subset of machine learning named deep learning (DL) has taken the world by storm. Based on neural networks, DL algorithms have […]

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Amazon Vice President of Machine LearningSwami Sivasubramanian speaks on stage at re:Invent.

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 […]

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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 […]

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New – Fully Serverless Batch Computing with AWS Batch Support for AWS Fargate

We launched AWS Batch on December 2016 as a fully managed batch computing service that enables developers, scientists and engineers to easily and efficiently run hundreds of thousands of batch computing jobs on AWS. With AWS Batch, you no longer need to install and manage batch computing software or server clusters to run your jobs. […]

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