AWS Machine Learning Blog

AWS recently released Model Server for Apache MXNet (MMS) v1.0, featuring a new API for managing the state of the service, which includes the ability to dynamically load models during runtime, to lower latency, and to have higher throughput. In this post, we will explore the new features and showcase the performance gains of the […]

Natural disasters like the 2017 Santa Rosa fires and Hurricane Harvey cost hundreds of billions of dollars in property damages every year, wreaking economic havoc in the lives of homeowners. Insurance companies do their best to evaluate affected homes, but it could take weeks before assessments are available and salvaging and protecting the homes can […]

Amazon Translate is a neural machine translation service that delivers fast, high-quality, and affordable language translation. Today, we are launching 113 new language pairs. Customers can now translate between currently supported languages, such as French to Spanish for example, with a single API request. With this update, we are expanding the number of supported language pairs […]

This post was reviewed June, 2022. An Amazon SageMaker notebook instance provides a Jupyter notebook app through a fully managed machine learning (ML) Amazon EC2 instance. Amazon SageMaker Jupyter notebooks are used to perform advanced data exploration, create training jobs, deploy models to Amazon SageMaker hosting, and test or validate your models. The notebook instance […]

Amazon SageMaker now supports running Batch Transform jobs in Amazon Virtual Private Cloud (Amazon VPC) and using AWS Key Management Service (AWS KMS). Amazon VPC allows you to control access to your machine learning (ML) model containers and data so that they are private and aren’t accessible over the internet. AWS KMS enables you to encrypt […]

April 2023 Update: Starting January 31, 2024, you will no longer be able to access AWS DeepLens through the AWS management console, manage DeepLens devices, or access any projects you have created. To learn more, refer to these frequently asked questions about AWS DeepLens end of life. August 30, 2023: Amazon Kinesis Data Analytics has been […]

Amazon Comprehend is a natural language processing (NLP) service that uses machine learning to find insights and relationships in text. The service does the following for you: Identifies the language of the text. Extracts key phrases, places, people, brands, or locations. Understands how positive or negative the text is. Analyzes text using tokenization and parts […]

April 2023 Update: Starting January 31, 2024, you will no longer be able to access AWS DeepLens through the AWS management console, manage DeepLens devices, or access any projects you have created. To learn more, refer to these frequently asked questions about AWS DeepLens end of life. AWS DeepLens is a deep-learning-enabled video camera for developers. It […]

Retailers have been using in-store video to analyze customer behaviors and demographics for many years.  Separate systems are commonly used for different tasks.  For example, one system would count the number of customers moving through a store, in which part of the store those customers linger and near which products.  Another system will hold the store layout, whilst yet […]

Amazon SageMaker now comes with a faster Pipe mode implementation, significantly accelerating the speeds at which data can be streamed from Amazon Simple Storage Service (S3) into Amazon SageMaker while training machine learning models. Pipe mode offers significantly better read throughput than the File mode that downloads data to the local Amazon Elastic Block Store […]