AWS FeedRun image classification with Amazon SageMaker JumpStart Last year, 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 hosts 196 computer vision models, 64 natural language processing (NLP) models, 18 pre-built end-to-end solutions, and 19 example…
AWS FeedManaging Security and Compliance for Your Journey to AWS with Wipro Cloud Application Risk Governance By Amit Verma, AWS Security Practice Head – Wipro By Bhavesh Kumar Bhatt, Cloud Security Practice Head – WiproBy Stephen Randolph, Sr. Partner Solutions Architect – AWSBy Tushar Agarwal, Sr. Partner Solutions Architect – AWS Most enterprises are at…
AWS FeedIncremental data matching using AWS Lake Formation and AWS Glue AWS Lake Formation provides a machine learning (ML) capability (FindMatches transform) to identify duplicate or matching records in your dataset, even when the records don’t have a common unique identifier and no fields match exactly. Customers across many industries have come to rely on…
AWS FeedArchitecture Monthly Magazine: Genomics The field of genomics has made huge strides in the last 20 years. Genomics organizations and researchers are rising to the many challenges we face today, and seeking improved methods for future needs. Amazon Web Services (AWS) provides an array of services that can help the genomics industry with securely…
AWS FeedImplement tenant isolation for Amazon S3 and Aurora PostgreSQL by using ABAC In software as a service (SaaS) systems, which are designed to be used by multiple customers, isolating tenant data is a fundamental responsibility for SaaS providers. The practice of isolation of data in a multi-tenant application platform is called tenant isolation. In…
AWS FeedAmazon SageMaker Pipeline introduces a automatic hyperparameter tuning step Amazon SageMaker Pipelines, the first purpose-built continuous integration and continuous delivery (CI/CD) service for machine learning (ML), is now integrated with SageMaker’s automatic model tuning capability. Customers can add a model tuning step (TuningStep) in their SageMaker Pipelines which will automatically invoke a hyperparameter tuning…