Best practices for viewing and querying Amazon SageMaker service quota usage

Amazon SageMaker customers can view and manage their quota limits through Service Quotas. In addition, they can view near real-time utilization metrics and create Amazon CloudWatch metrics to view and programmatically query SageMaker quotas. SageMaker helps you build, train, and deploy machine learning (ML) models with ease. To learn more, refer to Getting started with […]

How AWS Payments migrated from Redash to Amazon Redshift Query Editor v2

AWS Payments is part of the AWS Commerce Platform (CP) organization that owns the customer experience of paying AWS invoices. It helps AWS customers manage their payment methods and payment preferences, and helps customers make self-service payments to AWS. The Machine Learning, Data and Analytics (MLDA) team at AWS Payments enables data-driven decision-making across payments […]

Build custom code libraries for your Amazon SageMaker Data Wrangler Flows using AWS Code Commit

As organizations grow in size and scale, the complexities of running workloads increase, and the need to develop and operationalize processes and workflows becomes critical. Therefore, organizations have adopted technology best practices, including microservice architecture, MLOps, DevOps, and more, to improve delivery time, reduce defects, and increase employee productivity. This post introduces a best practice […]

Accelerating revenue growth with real-time analytics: Poshmark’s journey

This post was co-written by Mahesh Pasupuleti and Gaurav Shah from Poshmark. Poshmark is a leading social marketplace for new and secondhand styles for women, men, kids, pets, home, and more. By combining the human connection of physical shopping with the scale, ease, and selection benefits of Ecommerce, Poshmark makes buying and selling simple, social, […]

Accelerate Amazon SageMaker inference with C6i Intel-based Amazon EC2 instances

This is a guest post co-written with Antony Vance from Intel. Customers are always looking for ways to improve the performance and response times of their machine learning (ML) inference workloads without increasing the cost per transaction and without sacrificing the accuracy of the results. Running ML workloads on Amazon SageMaker running Amazon Elastic Compute […]

Extend geospatial queries in Amazon Athena with UDFs and AWS Lambda

Amazon Athena is a serverless and interactive query service that allows you to easily analyze data in Amazon Simple Storage Service (Amazon S3) and 25-plus data sources, including on-premises data sources or other cloud systems using SQL or Python. Athena built-in capabilities include querying for geospatial data; for example, you can count the number of […]

Amazon QuickSight helps TalentReef empower its customers to make more informed hiring decisions

This post is co-written with Alexander Plumb, Product Manager at Mitratech. TalentReef, now part of Mitratech, is a talent management platform purpose-built for location-based, high-volume hiring. TalentReef was acquired by Mitratech in August 2022 with the goal to combine TalentReef’s best-in-class systems with Mitratech’s expertise, technology, and global platform to ensure their customers’ hiring needs […]

Intelligently search your organization’s Microsoft Teams data source with the Amazon Kendra connector for Microsoft Teams

Organizations use messaging platforms like Microsoft Teams to bring the right people together to securely communicate with each other and collaborate to get work done. Microsoft Teams captures invaluable organizational knowledge in the form of the information that flows through it as users collaborate. However, making this knowledge easily and securely available to users can […]

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