AWS Partner Network (APN) Blog
Tag: Domino Data Lab
AI Governance with Domino Data Lab on AWS: From Policies to Practices
As AI governance becomes a pressing necessity, Domino Data Lab, in partnership with AWS, is bridging the gap between abstract policies and actionable practices. Domino’s Enterprise AI Platform on AWS empowers organizations to innovate confidently and responsibly by seamlessly integrating effective governance throughout the AI lifecycle, mitigating risks while driving business value.
How to Export a Model from Domino for Deployment in Amazon SageMaker
Data science is driving significant value for many organizations, including fueling new revenue streams, improving longstanding processes, and optimizing customer experience. Domino Data Lab empowers code-first data science teams to overcome these challenges of building and deploying data science at scale. Learn how to build and export a model from the Domino platform for deployment in Amazon SageMaker. Deploying models within Domino provides insight into the full model lineage.
Understanding the Data Science Life Cycle to Drive Competitive Advantage
Companies struggling with data science don’t understand the data science life cycle. As a result, they fall into the trap of the model myth. This is the mistake of thinking that because data scientists work in code, the same processes that works for building software will work for building models. Models are different, and the wrong approach leads to trouble. Domino Data Lab shares that organizations excelling at data science are those that understand it as a unique endeavor, requiring a new approach.
New AWS Solution Space Launches with 10 Customer-Ready Solutions
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.