Tag: Amazon Rekognition

Organizations often need business analysts and citizen data scientists to work with data scientists to create machine learning (ML) models, but they struggle to provide a common ground for collaboration. Newly enriched Dataiku Data Science Studio (DSS) and Amazon SageMaker capabilities answer this need, empowering a broader set of users by leveraging the managed infrastructure of Amazon SageMaker and combining it with Dataiku’s visual interface to develop models at scale.

A big challenge for enterprises is how to manage the growth of data in a cost-effective manner. CIOs are also looking for ways to get insights out of the data so their organizations can create actionable outcomes. Learn how the CloudArchive Direct feature of Cohesity’s DataPlatform with AWS analytics services to drive insights into customers’ NAS data. Cohesity is redefining data management to lower TCO while simplifying the way businesses manage and protect their data.

As mobile devices and 5G networks pave the way for diversified content consumption across the globe, the new global media trend poses new challenges to traditional broadcasting companies. MegazoneCloud’s customer, a global broadcaster based in South Korea, turned to the cloud for help transforming its media production system and providing leading-edge services to its audience. The customer adopted state-of-the-art, cloud-based media technology, and undertook an industry-leading digital transformation.

AWS introduced Amazon EventBridge partner event source integrations to showcase reference architectures and end-to-end use cases that help you get started quickly with integrating SaaS partners in your own applications. Fully open source, these solutions include code and AWS Serverless Application Model (SAM) templates that can be customized and extended to fit your application’s needs. The reference architectures include AWS Quick Starts and GitHub code to ease integration.

With rapid advancements in machine learning techniques over the past decade, intelligent decision-making and prediction systems are poised to transform productivity and lead to significant economic gains. KNIME provides visual data science tools to help data science teams rapidly build and deploy data-driven solutions that integrate with AWS decision support tools and services. Learn about the barriers to adoption of AI and the ways in which the KNIME tools remove those barriers.

Learn how to seamlessly integrate Amazon Rekognition with the Cloudinary platform, and build an application that automatically tags people in images with names. This solution learns people’s faces from photos uploaded to a “training” folder in Cloudinary. In many cases, a single photo of someone is enough for Amazon Rekognition to learn and then, later on, identify and tag that person. This works in most photograph scenes and even pictures with many other people in them.

Medical imaging is a key part of patient health records and clinical trial workflows. Many facilities still burn medical imaging on CDs, a time-consuming and error-prone process. Ambra Health’s automatic pixel de-identification feature uses Amazon Rekognition and Amazon Comprehend Medical APIs to allow customers to de-identify images and reduce error. Now, it’s easier than ever to deploy an integrated application fabric that elevates healthcare efficiency and care.

Amazon Rekognition makes it easy to add highly accurate image and video analysis to your applications. The service’s core functionality allowed Slalom, an APN Premier Consulting Partner, to create three personalized, interactive experiences for attendees at REALIZE, the company’s inaugural, one-day client summit in Chicago. Dive deep into how Slalom did it, and follow along with a how-to so you can learn to do it yourself.

Learn how to create a sample custom Box Skill by using Amazon Rekognition Image and AWS Lambda to apply computer vision to image files in Box. This new metadata allows you to quickly find images based on keyword searches, or find images that may be inappropriate and should be moderated. With services like Amazon Transcribe, Amazon Translate, Amazon Comprehend, Amazon Rekognition Video, and Amazon SageMaker, there’s no limit to the ways you can apply AI/ML to your media files.

The AWS Service Broker is an open source project that allows native AWS services to be exposed directly through application platforms, such as Red Hat OpenShift Container Platform. Developers are able to provision and expose AWS through the Service Catalog, CLI, or API without needing to interact with the AWS console, or without having extensive knowledge of AWS. In response to customer feedback, we have added new features to AWS Service Broker for OpenShift and Kubernetes.