Tag: Amazon Rekognition

With exponential increases in the amount of visual data such as images and videos being generated, image analytics is fast becoming a major business driver for many organizations. The Deloitte Image Recognition Framework is a cloud-based image recognition platform leveraging machine learning to automatically distinguish between two images. It helps customers deploy image recognition and analytics solutions and customize it per their business requirements.

Despite the investments and commitment from leadership, many organizations are yet to realize the full potential of artificial intelligence (AI) and machine learning (ML). How can data science and analytics teams tame complexity and live up to the expectations placed on them? MLOps provides some answers. Hear from AWS Premier Consulting Partner Reply how you can “glue” the various components of MLOps together to build an MLOps solution using AWS managed services.

Organizations need a comprehensive data management solution that includes data quality, cleansing, de-duplication, and curation capabilities. After consolidating trusted golden records, they need to enforce governance requirements and track changes over time. Semarchy’s xDM platform is an innovation in multi-vector Main Data Management (MDM) that leverages smart algorithms and material design to simplify data stewardship, governance, and integration.

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.