Cloudera Blog
We are thrilled to announce the general availability of the Cloudera AI Inference service, powered by NVIDIA NIM microservices, part of the NVIDIA AI Enterprise platform, to accelerate generative AI deployments for enterprises. This service supports a range of optimized AI models, enabling seamless and scalable AI inference. Background The generative AI landscape is evolving […] Read blog post
Cloudera Blog
In an era where artificial intelligence (AI) is reshaping enterprises across the globe—be it in healthcare, finance, or manufacturing—it’s hard to overstate the transformation that AI has had on businesses, regardless of industry or size. At Cloudera, we recognize the urgent need for bold steps to harness this potential and dramatically accelerate the time to […] Read blog post
Midwest.io 2014 - Building a Production Machine Learning Infrastructure - Josh Wills
This talk was given at Midwest.io 2014. Cloudera's Data Science Team has a simple mission: build an analytics infrastructure so awesome that it makes Google's Ads Quality Team seethe with jealousy. To that end, I'll give an overview of Cloudera's current data science tools, including Oryx and Spark for building and serving machine learning models, Gertrude for multivariate testing, and Impala for
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GitHub - OryxProject/oryx: Oryx 2: Lambda architecture on Apache Spark, Apache Kafka for real-time large scale machine learning
Spark Panel Discussion with Cloudera, MapR & Pivotal - insideAI News
