Maintaining multiple machine learning models across different teams can be challenging. Having a centralized platform to monitor and manage them can significantly reduce operational overhead and improve efficiency. Learn how the models trained and deployed in Amazon SageMaker can be monitored by DataRobot in a highly scalable fashion. In this way, customers can monitor both DataRobot-originated models and SageMaker-originated models under a single pane of glass.
Say Hello to 176 AWS Competency, Service Delivery, Service Ready, and MSP Partners Added or Renewed in May
We are excited to highlight 176 AWS Partners that received new or renewed designations in May for our global AWS Competency, AWS Managed Service Provider (MSP), AWS Service Delivery, and AWS Service Ready programs. These designations span workload, solution, and industry, and help AWS customers identify top AWS Partners that can deliver on core business objectives. AWS Partners are focused on your success, helping customers take full advantage of the business benefits AWS has to offer.
Operationalizing machine learning models can be a challenge due to lack of established ML architecture and its integration with the existing landscape. DataRobot integrates with AWS and provides the flexibility for a model trained in DataRobot to be deployed on AWS services with centralized model governance, management, and monitoring. Learn how the DataRobot AutoML platform orchestrates the complete model development and training lifecycle.
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).
As the old saying goes, “You never get a second chance to make a first impression.” Customer trust is hard-earned and easily lost. Properly architecting a scalable and secure SaaS-based product is just as important as feature development and sales. No one wants to fail on Day 1— you worked too hard to get there. Get a comprehensive introduction to the common ways in which customers consume cloud-based SaaS models, and explore the different ways in which ISVs sell their software products to customers.
AWS Solution Space allows AWS Competency Partners to showcase customer-ready solutions based on architectures validated by AWS. These are quick, cost effective, repeatable solutions meant to create new business leading to production workloads. Customers can also request AWS support for launching each solution. At launch, we are featuring 10 customer-ready solutions: 5 for Big Data, 3 for Machine Learning, one for Security, and one for End User Computing.