Category: Amazon SageMaker

July 2023: This post was reviewed for accuracy. 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). JumpStart provides one-click fine-tuning and deployment of a wide variety of pre-trained models across popular ML tasks, as […]

In this post, we will demonstrate how to securely launch notebook instances in a private subnet of an Amazon Virtual Private Cloud (Amazon VPC), with internet access disabled, and to securely connect to Amazon Simple Storage Service (Amazon S3) using VPC endpoints. This post is for network and security architects that support decentralized data science […]

April 2023: This post was reviewed and updated with Amazon SageMaker Canvas’s new features and UI changes. Machine learning (ML) helps organizations increase revenue, drive business growth, and reduce cost by optimizing core business functions across multiple verticals, such as demand forecasting, credit scoring, pricing, predicting customer churn, identifying next best offers, predicting late shipments, […]

September 2023: This post was reviewed and updated for accuracy. Many software as a service (SaaS) providers across various industries are adding machine learning (ML) and artificial intelligence (AI) capabilities to their SaaS offerings to address use cases like personalized product recommendation, fraud detection, and accurate demand protection. Some SaaS providers want to build such […]

March 2025: This post was reviewed and updated for accuracy. 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 […]

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 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 […]

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 […]