AWS Machine Learning Blog

As the touchpoints customers use to engage with brands move to an increasingly complex mixture of digital and real-life interactions, you’re faced with the daunting task of delighting your customers with personalized experiences that hit the mark across these channels. Customer expectations are evolving as well. Today’s customers quickly lose patience with brands that can’t […]

Tens of thousands of customers rely on AWS for building machine learning (ML) applications. Customers like Airbnb and Pinterest use AWS to optimize their search recommendations, Lyft and Toyota Research Institute to develop their autonomous vehicle programs, and Capital One and Intuit to build and deploy AI-powered customer assistants. AWS offers the broadest and deepest […]

December 2020 Update – This blog post now also covers how the Medical Transcription Analysis can also be used to store and retrieve medical transcriptions and relevant information using Amazon DynamoDB and Amazon S3 and how all of this data can be analyzed using Amazon Athena. The healthcare industry is a highly regulated and complex […]

This is a guest blog post by Sungoh Park, a big data analyst at Lotte Mart. In their own words, “Lotte Mart, a division of Lotte Co., Ltd., is a leading South Korean retailer that sells a variety of groceries, clothing, toys, electronics, and other goods.” Consumers today have many options for purchasing daily necessities; […]

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 Fraud Detector is a fully managed service that makes it easy to identify potentially fraudulent online activities, such as the creation of fake accounts or online payment fraud. Unlike general-purpose machine learning (ML) packages, Amazon Fraud Detector is designed specifically to detect fraud. Amazon Fraud Detector combines your data, the latest in ML science, […]

Amazon Web Services (AWS) is happy to announce the general availability of Notebooks within Amazon SageMaker Studio. Amazon SageMaker Studio supports on-the-fly selection of machine learning (ML) instance types, optimized and pre-packaged Amazon SageMaker Images, and sharing of Jupyter notebooks. You can switch a notebook from using a kernel on one instance type to another, […]

Support for AWS DeepComposer will be ending soon. Please see Support for AWS DeepComposer ending soon for more details. 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 […]

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. Many industries, including retail, manufacturing, and healthcare, are adopting […]

Machine Learning (ML) impacts industries around the globe, from financial services industry (FSI) and manufacturing  to autonomous vehicles and space exploration. ML is no longer just an aspirational technology exclusive to academic and research institutions; it has evolved into a mainstream technology that has the potential to benefit organizations of all sizes. However, a lack […]