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AWS DeepComposer – Now Generally Available With New Features

AWS DeepComposer, a creative way to get started with machine learning, was launched in preview at AWS re:Invent 2019. Today, I’m extremely happy to announce that DeepComposer is now available to all AWS customers, and that it has…
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AWS Named as a Leader in Gartner’s Magic Quadrant for Cloud AI Developer Services

Last week I spoke to executives from a large AWS customer and had an opportunity to share aspects of the Amazon culture with them. I was able to talk to them about our Leadership Principles and our Working Backwards model. They asked, as…
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Now available in Amazon Transcribe: Automatic Redaction of Personally Identifiable Information

Launched at AWS re:Invent 2017, Amazon Transcribe is an automatic speech recognition (ASR) service that makes it easy for AWS customers to add speech-to-text capabilities to their applications. At the time of writing, Transcribe supports 31…
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New – Amazon Comprehend Medical Adds Ontology Linking

Amazon Comprehend is a natural language processing (NLP) service that uses machine learning to find insights in unstructured text. It is very easy to use, with no machine learning experience required. You can customize Comprehend for…
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Amazon SageMaker Studio: The First Fully Integrated Development Environment For Machine Learning

Today, we’re extremely happy to launch Amazon SageMaker Studio, the first fully integrated development environment (IDE) for machine learning (ML).We have come a long way since we launched Amazon SageMaker in 2017, and it is shown…
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Amazon SageMaker Debugger – Debug Your Machine Learning Models

Today, we’re extremely happy to announce Amazon SageMaker Debugger, a new capability of Amazon SageMaker that automatically identifies complex issues developing in machine learning (ML) training jobs.Building and training ML models…
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Amazon SageMaker Model Monitor – Fully Managed Automatic Monitoring For Your Machine Learning Models

Today, we’re extremely happy to announce Amazon SageMaker Model Monitor, a new capability of Amazon SageMaker that automatically monitors machine learning (ML) models in production, and alerts you when data quality issues appear.The…
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Amazon SageMaker Processing – Fully Managed Data Processing and Model Evaluation

Today, we’re extremely happy to launch Amazon SageMaker Processing, a new capability of Amazon SageMaker that lets you easily run your preprocessing, postprocessing and model evaluation workloads on fully managed infrastructure.Training…
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Amazon SageMaker Autopilot – Automatically Create High-Quality Machine Learning Models With Full Control And Visibility

Today, we’re extremely happy to launch Amazon SageMaker Autopilot to automatically create the best classification and regression machine learning models, while allowing full control and visibility.In 1959, Arthur Samuel defined machine…
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Amazon SageMaker Experiments – Organize, Track And Compare Your Machine Learning Trainings

Today, we’re extremely happy to announce Amazon SageMaker Experiments, a new capability of Amazon SageMaker that lets you organize, track, compare and evaluate machine learning (ML) experiments and model versions.ML is a highly iterative…