AWS Machine Learning Blog

Category: Announcements

Introducing Amazon CodeWhisperer, the ML-powered coding companion

We are excited to announce Amazon CodeWhisperer, a machine learning (ML)-powered service that helps improve developer productivity by providing code recommendations based on developers’ natural comments and prior code. With CodeWhisperer, developers can simply write a comment that outlines a specific task in plain English, such as “upload a file to S3.” Based on this, […]

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Amazon SageMaker Notebook Instances now support configuring and restricting IMDS versions

Today, we’re excited to announce that Amazon SageMaker now supports the ability to configure Instance Metadata Service Version 2 (IMDSv2) for Notebook Instances, and for administrators to control the minimum version with which end-users create new Notebook Instances. You can now choose IMDSv2 only for your new and existing SageMaker Notebook Instances to take advantage […]

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Run automatic model tuning with Amazon SageMaker JumpStart

In December 2020, AWS announced the general availability of Amazon SageMaker JumpStart, a capability of Amazon SageMaker that helps you quickly and easily get started with machine learning (ML). In March 2022, we also announced the support for APIs in JumpStart. JumpStart provides one-click fine-tuning and deployment of a wide variety of pre-trained models across […]

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season-trend decomposition

Prepare time series data with Amazon SageMaker Data Wrangler

Time series data is widely present in our lives. Stock prices, house prices, weather information, and sales data captured over time are just a few examples. As businesses increasingly look for new ways to gain meaningful insights from time-series data, the ability to visualize data and apply desired transformations are fundamental steps. However, time-series data […]

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Hybrid ML

Introducing hybrid machine learning

Gartner predicts that by the end of 2024, 75% of enterprises will shift from piloting to operationalizing artificial intelligence (AI), and the vast majority of workloads will end up in the cloud in the long run. For some enterprises that plan to migrate to the cloud, the complexity, magnitude, and length of migrations may be […]

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Your guide to AI and ML at AWS re:Invent 2021

It’s almost here! Only 9 days until AWS re:Invent 2021, and we’re very excited to share some highlights you might enjoy this year. The AI/ML team has been working hard to serve up some amazing content and this year, we have more session types for you to enjoy. Back in person, we now have chalk […]

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Fully customizable action space now available on the AWS DeepRacer console

AWS DeepRacer is the fastest way to get rolling with machine learning (ML) through a global racing league, cloud-based 3D racing simulator, and fully autonomous 1/18th scale race car driven by reinforcement learning. Starting today, the model action space is fully customizable yet simplified with new dynamic graphics so developers have greater control and can […]

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Amazon SageMaker notebook instances now support Amazon Linux 2

February 8th, 2022: Updated with AWS CloudFormation support to create an Amazon Linux 2 based SageMaker notebook instance. Today, we’re excited to announce that Amazon SageMaker notebook instances support Amazon Linux 2. You can now choose Amazon Linux 2 for your new SageMaker notebook instance to take advantage of the latest update and support provided […]

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Announcing model improvements and lower annotation limits for Amazon Comprehend custom entity recognition

Update August 3, 2022: Minimum requirements for training entity recognizers have been further reduced. You can now build a custom entity recognition model with as few as three documents and 25 annotations per entity type. Additional details available in the Amazon Comprehend Guidelines and quotas webpage and in the blog post announcing the limit reduction. […]

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DeepLearning.AI, Coursera, and AWS launch the new Practical Data Science Specialization with Amazon SageMaker

Amazon Web Services (AWS), Coursera, and DeepLearning.AI are excited to announce Practical Data Science, a three-course, 10-week, hands-on specialization designed for data professionals to quickly learn the essentials of machine learning (ML) in the AWS Cloud. DeepLearning.AI was founded in 2017 by Andrew Ng, an ML and education pioneer, to fill a need for world-class […]

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