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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…
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Now Available on Amazon SageMaker: The Deep Graph Library

Today, we’re happy to announce that the Deep Graph Library, an open source library built for easy implementation of graph neural networks, is now available on Amazon SageMaker.In recent years, Deep learning has taken the world by…
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AWS DeepComposer – Compose Music with Generative Machine Learning Models

Today, we’re extremely happy to announce AWS DeepComposer, the world’s first machine learning-enabled musical keyboard. Yes, you read that right.Machine learning (ML) requires quite a bit of math, computer science, code, and…
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New for Amazon Aurora – Use Machine Learning Directly From Your Databases

Machine Learning allows you to get better insights from your data. But where is most of the structured data stored? In databases! Today, in order to use machine learning with data in a relational database, you need to develop a custom application…