Category: Amazon Machine Learning

Organizations that have foresight into their business have a competitive advantage. Advanced analytics that enable foresight have historically required scarce resources to develop predictive models using techniques like machine learning. Traditionally, this is a difficult endeavor, but recent progress in ML automation has made democratization of ML a possibility. Learn about the value of augmenting analytics with ML through the Amazon SageMaker for Tableau Quick Start.

Machine learning allows users to drive insights about their business, and the AutoML approach speeds up this process through the automation of ML pipeline steps. Learn how Domo created AutoML capabilities powered by Amazon SageMaker Autopilot, which is a fully managed AWS solution that automatically creates, trains, and tunes the best classification and regression ML models based on the data provided by a customer.

Achieving “speed of thought” or instant analytics on large data sets is a key challenge for business intelligence platforms. Traditionally, data engineers would design and deliver an optimized, aggregated subset of the data to a data warehouse to drive the visualization. This can often take weeks of development and testing or incur significant infrastructure costs. Learn how Indexima uses machine learning and hyper indexes to automate this process and accelerate analytics by up to 1000x across a full data set on Amazon S3.

Artificial intelligence (AI) and machine learning (ML) are maturing rapidly. According to Gartner, 75% of enterprises will shift from piloting to operationalizing AI by 2024. That’s why we are expanding the AWS Machine Learning Competency to help customers identify and engage qualified AWS Partners that have deep technical expertise and proven customer success in the areas of Applied AI and Machine Learning Operations (MLOps).

To help safeguard workplaces from the pandemic, TensorIoT developed SafetyVisor, a suite of machine learning tools that can operate independently or in tandem with existing business infrastructure to monitor safety gear usage (like masks) and social distancing. SafetyVisor’s computer vision models are designed to work with your existing cameras, and the entire solution is built utilizing a flexible architecture to facilitate easy deployment and use.

DXC Technology created a serverless artificial intelligence-powered solution called CoDetect to help detect manifestations of COVID-19 (and other medical conditions) in CT scans. Learn about the AWS services DXC chose for this solution, and explore two functional use cases that demonstrate the benefits of DXC’s CoDetect design and implementation approach. CoDetect is a web-based app that allows end users to submit CT scan studies for an AI model analysis.

Many organizations have started applying machine learning and artificial intelligence expertise to scale customer communications and accelerate research during the COVID-19 pandemic. Onica has been actively involved in these efforts, leveraging AWS technologies to help decision makers navigate this pandemic. In this post, dive into the technical details of two COVID-19-related solutions Onica has produced and learn about their results and impact.

Scaling doctors’ expertise through artificial intelligence (AI) and machine learning (ML) provides an affordable and accurate solution, giving millions of infants equal access to eye screening. Learn how Pr3vent, a medical AI company founded by ophthalmologists, teamed up with AWS Machine Learning Competency Partner Provectus to develop an advanced disease screening solution powered by deep learning that detects pathology and signs of possible abnormalities in the retinas of newborns.

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.

Edge computing is a new paradigm in which the resources of a small data center are placed at the edge of the internet, in close proximity to mobile devices, sensors, and end users. Learn about the Physical Distancing Video Analytics Solution (VAS) on campus private 4G/5G networks that was developed utilizing AWS edge services in partnership with Carnegie Mellon University’s Open Edge Computing Initiative, Megh Computing’s Video Analytics Solution, and Federated Wireless Private Network Connectivity as a Service.