Category: Amazon SageMaker

Today, social media is a huge source of news. Users rely on platforms like Facebook and Twitter to consume news. For certain industries such as insurance companies, first respondents, law enforcement, and government agencies, being able to quickly process news about relevant events occurring can help them take action while these events are still unfolding. […]

This is a guest blog post by Danny Brock, Rajeev Govindan and Krishnaram Kenthapadi at Fiddler AI. Your Amazon SageMaker models are live. They’re handling millions of inferences each day and driving better business outcomes for your company. They’re performing exactly as well as the day they were launched. Er, wait. Are they? Maybe. Maybe […]

Data scientists often work towards understanding the effects of various data preprocessing and feature engineering strategies in combination with different model architectures and hyperparameters. Doing so requires you to cover large parameter spaces iteratively, and it can be overwhelming to keep track of previously run configurations and results while keeping experiments reproducible. This post walks […]

Organizations are increasingly building and using machine learning (ML)-powered solutions for a variety of use cases and problems, including predictive maintenance of machine parts, product recommendations based on customer preferences, credit profiling, content moderation, fraud detection, and more. In many of these scenarios, the effectiveness and benefits derived from these ML-powered solutions can be further […]

LiDAR is a key enabling technology in growing autonomous markets, such as robotics, industrial, infrastructure, and automotive. LiDAR delivers precise 3D data about its environment in real time to provide “vision” for autonomous solutions. For autonomous vehicles (AVs), nearly every carmaker uses LiDAR to augment camera and radar systems for a comprehensive perception stack capable […]

Optical character recognition (OCR) is the task of converting printed or handwritten text into machine-encoded text. OCR has been widely used in various scenarios, such as document electronization and identity authentication. Because OCR can greatly reduce the manual effort to register key information and serve as an entry step for understanding large volumes of documents, […]

October 2023: This post was reviewed and updated for accuracy. Machine learning (ML) is disrupting a lot of industries at an unprecedented pace. The healthcare and life sciences (HCLS) industry has been going through a rapid evolution in recent years embracing ML across a multitude of use cases for delivering quality care and improving patient […]

If you use the default lifecycle configuration for your domain or user profile in Amazon SageMaker Studio and use Amazon SageMaker Data Wrangler for data preparation, then this post is for you. In this post, we show how you can create a Data Wrangler flow and use it for data preparation in a Studio environment […]

You can access Amazon SageMaker Studio notebooks from the Amazon SageMaker console via AWS Identity and Access Management (IAM) authenticated federation from your identity provider (IdP), such as Okta. When a Studio user opens the notebook link, Studio validates the federated user’s IAM policy to authorize access, and generates and resolves the presigned URL for […]

In part 1 of this series, we demonstrated how to resolve an Amazon SageMaker Studio presigned URL from a corporate network using Amazon private VPC endpoints without traversing the internet. In this post, we will continue to build on top of the previous solution to demonstrate how to build a private API Gateway via Amazon API […]