AWS Machine Learning Blog

Amazon SageMaker Autopilot is an automated machine learning (AutoML) solution that performs all the tasks you need to complete an end-to-end machine learning (ML) workflow. It explores and prepares your data, applies different algorithms to generate a model, and transparently provides model insights and explainability reports to help you interpret the results. Autopilot can also […]

In this post, we present a solution for digitizing transactional documents using Amazon Textract and incorporate a human review using Amazon Augmented AI (A2I). You can find the solution source at our GitHub repository. Organizations must frequently process scanned transactional documents with structured text so they can perform operations such as fraud detection or financial […]

Data lakes have become the norm in the industry for storing critical business data. The primary rationale for a data lake is to land all types of data, from raw data to preprocessed and postprocessed data, and may include both structured and unstructured data formats. Having a centralized data store for all types of data […]

Amazon Comprehend is a natural language processing (NLP) service that uses machine learning (ML) to discover insights from text. As a fully managed service, Amazon Comprehend requires no ML expertise and can scale to large volumes of data. Amazon Comprehend provides several different APIs to easily integrate NLP into your applications. You can simply call […]

Amazon SageMaker Autopilot automatically builds, trains, and tunes the best machine learning (ML) models based on your data, while allowing you to maintain full control and visibility. We have recently announced support for time series data in Autopilot. You can use Autopilot to tackle regression and classification tasks on time series data, or sequence data […]

With an Amazon SageMaker Domain, you can onboard users with an AWS Identity and Access Management (IAM) execution role different than the Domain execution role. In such case, the onboarded Domain user can’t create projects using templates and Amazon SageMaker JumpStart solutions. This post outlines an automated approach to enable JumpStart for Domain users with […]

February 2023 Update: Console access to the AWS Data Pipeline service will be removed on April 30, 2023. On this date, you will no longer be able to access AWS Data Pipeline though the console. You will continue to have access to AWS Data Pipeline through the command line interface and API. Please note that […]

This post is authored by Satish Jha, Intelligent Automation Manager, Matt Docherty, Data Science Manager, Jayesh Muley, Associate Consultant and Tapan Vora, Rapid Prototyping, from ZS Associates. At ZS Associates, we do a significant amount of qualitative market research. The work involves interviewing relevant subjects (such as healthcare professionals and sales representatives) and developing bespoke […]

November 2022: This post is now obsolete. Please refer to the latest blog post Easy and accurate forecasting with AutoGluon-TimeSeries. Whether you’re allocating resources more efficiently for web traffic, forecasting patient demand for staffing needs, or anticipating sales of a company’s products, forecasting is an essential tool across many businesses. One particular use case, known […]

At the 2021 AWS re:Invent conference in Las Vegas, we demoed Read For Me at the AWS Builders Fair—a website that helps the visually impaired hear documents. For better quality, view the video here. Adaptive technology and accessibility features are often expensive, if they’re available at all. Audio books help the visually impaired read. Audio […]