Tag: Amazon SageMaker Studio

Featurization is one of the most difficult problems in machine learning. Learn how graph features engineered in Neo4j can be used in a supervised learning model trained with Amazon SageMaker. These novel graph features can improve model performance beyond what’s possible with more traditional approaches. Together, these components offer a graph platform that can be used to understand graph data and operationalize graph use cases.

Firms spend substantial efforts to identify and collect quality data streams from different sources. However, identifying and interpreting energy, water, or gas usage patterns and consumption types is sometimes insufficient. In this post, you’ll learn how Storm Reply, combining industry knowledge with its expertise in the development of data analytics platforms in AWS, can help customers in the design, development, and maintenance of secure serverless IoT big data platforms with a focus on sustainability.

Learn now Provectus looked into how machine learning models were prototyped and evaluated at VTS, and then delivered a template-based solution enabling their data scientists to more easily create Amazon SageMaker jobs, pipelines, endpoints, and other AWS resources. The resulting coherent set of templates, with usage cookbook and extension guidelines, was applied successfully on an ML model that predicted leasing outcomes.

OneLogin, an AWS Security Competency Partner, provides an identity platform for secure, scalable, and smart experiences that connects people to technology. Learn about all of the integrations available between OneLogin and AWS. Through these integrations, OneLogin enables you to seamlessly authenticate into AWS managed services across various domains, including analytics, compute, serverless, security, management and governance, and more.