AWS Machine Learning Blog

Category: Analytics

The Intel®3D Athlete Tracking (3DAT) scalable architecture deploys pose estimation models using HAQM Kinesis Data Streams and HAQM EKS

This blog post is co-written by Jonathan Lee, Nelson Leung, Paul Min, and Troy Squillaci from Intel.  In Part 1 of this post, we discussed how Intel®3DAT collaborated with AWS Machine Learning Professional Services (MLPS) to build a scalable AI SaaS application. 3DAT uses computer vision and AI to recognize, track, and analyze over 1,000 […]

Control access to HAQM SageMaker Feature Store offline using AWS Lake Formation

This post was last reviewed and updated June, 2022 with revised feature groups (tables) and features (columns) permissions. You can establish feature stores to provide a central repository for machine learning (ML) features that can be shared with data science teams across your organization for training, batch scoring, and real-time inference. Data science teams can […]

Receive notifications for image analysis with HAQM Rekognition Custom Labels and analyze predictions

HAQM Rekognition Custom Labels is a fully managed computer vision service that allows developers to build custom models to classify and identify objects in images that are specific and unique to your business. Rekognition Custom Labels doesn’t require you to have any prior computer vision expertise. You can get started by simply uploading tens of […]

Automate a shared bikes and scooters classification model with HAQM SageMaker Autopilot

February 9, 2024: HAQM Kinesis Data Firehose has been renamed to HAQM Data Firehose. Read the AWS What’s New post to learn more. HAQM SageMaker Autopilot makes it possible for organizations to quickly build and deploy an end-to-end machine learning (ML) model and inference pipeline with just a few lines of code or even without […]

Process HAQM Redshift data and schedule a training pipeline with HAQM SageMaker Processing and HAQM SageMaker Pipelines

Customers in many different domains tend to work with multiple sources for their data: object-based storage like HAQM Simple Storage Service (HAQM S3), relational databases like HAQM Relational Database Service (HAQM RDS), or data warehouses like HAQM Redshift. Machine learning (ML) practitioners are often driven to work with objects and files instead of databases and […]

Bring Your HAQM SageMaker model into HAQM Redshift for remote inference

July 2024: This post was reviewed and updated for accuracy. HAQM Redshift, a fast, fully managed, widely used cloud data warehouse, natively integrates with HAQM SageMaker for machine learning (ML). Tens of thousands of customers use HAQM Redshift to process exabytes of data every day to power their analytics workloads. Data analysts and database developers […]

Build a system for catching adverse events in real-time using HAQM SageMaker and HAQM QuickSight

Social media platforms provide a channel of communication for consumers to talk about various products, including the medications they take. For pharmaceutical companies, monitoring and effectively tracking product performance provides customer feedback about the product, which is vital to maintaining and improving patient safety. However, when an unexpected medical occurrence resulting from a pharmaceutical product […]

Translate, redact, and analyze text using SQL functions with HAQM Redshift, HAQM Translate, and HAQM Comprehend

You may have tables in your HAQM Redshift data warehouse or in your HAQM Simple Storage Service (HAQM S3) data lake full of records containing customer case notes, product reviews, and social media messages, in many languages. Your task is to identify the products that people are talking about, determine if they’re expressing happy thoughts […]

Use the AWS Cloud for observational life sciences studies

In this post, we discuss how to use the AWS Cloud and its services to accelerate observational studies for life sciences customers. We provide a reference architecture for architects, business owners, and technology decision-makers in the life sciences industry to automate the processes in clinical studies. Observational studies lead the way in research, allowing you […]

How Intel Olympic Technology Group built a smart coaching SaaS application by deploying pose estimation models – Part 1

February 9, 2024: HAQM Kinesis Data Firehose has been renamed to HAQM Data Firehose. Read the AWS What’s New post to learn more. The Intel Olympic Technology Group (OTG), a division within Intel focused on bringing cutting-edge technology to Olympic athletes, collaborated with AWS Machine Learning Professional Services (MLPS) to build a smart coaching software […]