AWS News Blog
Author: Julien Simon
As an Artificial Intelligence & Machine Learning Evangelist for EMEA, Julien focuses on helping developers and enterprises bring their ideas to life.
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 in the growing number of customers using the service. However, the ML development workflow is still very iterative, […]
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 is a mix of science and craft (some would even say witchcraft). From collecting and preparing data sets to experimenting with different algorithms […]
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 first thing I learned when I started working with data is that there is no such thing as paying too much […]
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 an accurate machine learning (ML) model requires many different steps, but none is potentially more important than preprocessing your data set, e.g.: Converting […]
Amazon SageMaker Autopilot – Automatically Create High-Quality Machine Learning Models With Full Control And Visibility
Update September 30, 2021 – This post has been edited to remove broken links. 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 learning as the ability for computers to learn without being […]
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 process. During the course of a single project, data scientists and ML engineers routinely train thousands of different models in […]
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 storm thanks to its uncanny ability to extract elaborate patterns from complex data, such as free-form text, […]
Amazon Transcribe Medical – Real-Time Automatic Speech Recognition for Healthcare Customers
In 2017, we launched Amazon Transcribe, an automatic speech recognition service that makes it easy for developers to add speech-to-text capability to their applications: today, we’re extremely happy to extend it to medical speech with Amazon Transcribe Medical. When I was a child, my parents – both medical doctors – often spent evenings recording letters and exam […]