Our blog series continues! In this blog, we'll provide you with 3 easy ways #datascience teams can get started with GPUs for powering #deeplearning models in Cloudera Machine Learning & demonstrate one of the options to get you started. @NVIDIAAI
https://t.co/2yMVfB8GSX
[NEW] Applied Machine Learning Prototypes in Cloudera Machine Learning now available!
AMPs are a revolutionary way to accelerate your #ML initiatives, learn more about them here: https://t.co/dt3TlKnBbU #Machinelearning#datascience
"The imperative to deliver meaningful change and value through innovation is why the Data for Enterprise AI category at the #DataImpactAwards has never been more of the moment than it is today." Learn more about the category here - https://t.co/jcJ2vSkKHG #AI
3/ CML integrates the incredible assets (ArcViz from @ArcadiaData - we were lucky to join hands + incredible talent/leadership) for visual analytical apps to truly democratize creation, curation and consumption of ML.
(Also, CDW - warehouse offering, has the same benefits)
2/ CML provides enterprise grade ML Ops and leverages CDP's SDX capabilities for comprehensive data security and governance - for both data and ML models - across the entire data life-cycle (streaming, data transformation & prediction).
1/ Cloudera Machine Learning (CML) service is a fundamental part of the overall data platform that is CDP, as is available today on @AWSCloud, @Azure and on-premise Private Cloud via @RedHat@OpenShift. A fully hybrid and cloud-native service.