Tag: Amazon SageMaker
In the financial services industry, detecting fraud is a complex process. For any given transaction or activity, the system needs to decide whether it’s fraudulent or not and take action within seconds. With Redis Enterprise Cloud‘s sub-millisecond latency speeds, up to five 9’s of availability, linear scalability, and multiple data model support coupled with the global cloud infrastructure support of AWS, organizations can benefit from building a real-time fraud detection system to manage and control fraud.
Organizations have matured and have overcome the initial hurdles of proving the capabilities of AI. The challenge now is operationalizing AI and building engineering excellence to successfully adopt and manage machine learning at scale. Learn how Quantiphi assisted Venterra Realty in bringing in the best ML solution development and deployment practices through NeuralOps—a framework built on Amazon SageMaker.
In computer vision applications, the transmission of video data to the cloud for analysis can result in added delays due to various contributing factors such as queuing, propagation, and network latency. Learn how the Nordcloud team, in collaboration with AWS, has designed a “Computer Vision at the Edge” solution based on AWS Panorama. It caters to organizations seeking low-latency decision making without the burden of managing complex technology.
Metal Toad has been working with major entertainment brands for decades, including keeping some of the highest-profile media sites live under unique traffic conditions. Keeping these sites up and running is one of Metal Toad’s superpowers, but the AWS Digital Customer Experience Competency Partner couldn’t do it without the tools provided by AWS. Explore some of the strategies Metal Toad deployed to protect a customer’s site during an event where failure was not an option.
Amazon Redshift is a column-oriented database management system that stores data in columns, making it quicker to analyze data. The platform also performs a continuous backup of data, eliminating the risk of losing data or the need to plan for backup hardware. Learn how Hexaware’s automated platform, Amaze for Data & AI, transforms on-premises data warehouse ecosystems to the cloud while ensuring business keeps running smoothly and uninterrupted.
Many organizations derive business understanding and new insights through content analytics and intelligence. Wipro’s email automation framework leverages machine learning services from AWS that enable organizations to extract data from emails and provide automated instructions which enhance accuracy and improve staff productivity. This solution supports data extraction from the mailbox (email body and attachments) and validates and prioritizes based on the urgency of emails.
Learn how equipment operators can build a predictive maintenance solution using AutoML and no-code tools powered by AWS. This type of solution delivers significant gains to large-scale industrial systems and mission-critical applications where the costs associated with machine failure or unplanned downtime can be high. The design of this solution is based on the experience of Grid Dynamics with manufacturing clients.
Thank you for joining us in Las Vegas for AWS re:Invent 2022! We hope you enjoyed all of the educational content and big announcements. If you missed anything or just want to recap, we have rounded up the most relevant launches, program updates, and educational content available for the AWS Partner community, including the Partner Keynote with Ruba Borno. Reminder that you can watch on-demand re:Invent keynotes, leadership sessions, breakouts, and more.
We’re excited to announce the launch of the Amazon SageMaker Ready specialization for AWS Partners with Amazon SageMaker software offerings. Through this specialization, customers can identify software solutions that integrate with Amazon SageMaker—allowing them to seamlessly solve use cases and innovate with machine learning. Software offerings include data platforms, data pre-processing and feature stores, ML frameworks, MLOps tools, and business decisioning and applications.
Enterprises are building data analysis capabilities to extract information captured in data, develop an understanding of their business, and channel efforts towards customer centricity. This post explains the need for operational analytics and how it can be achieved with MongoDB Atlas and Amazon Redshift. MongoDB is an AWS Data and Analytics Competency Partner and developer data platform company empowering innovators to unleash the power of software and data.