Cloudera (NYSE: CLDR), the enterprise data cloud company, today launched Cloudera Machine Learning, the enterprise machine learning service for the new Cloudera Data Platform. Cloudera Machine Learning makes it easy for IT to say yes to self-service data science for business at scale.
Cloudera Machine Learning enables enterprise data science in the cloud.
“With Cloudera Machine Learning, businesses can rapidly deploy new ML Workspaces or virtual machine learning environments for teams in a few clicks, providing self-service access to the shared data and tools required for end-to-end machine learning workflows, anywhere,” said Priyank Patel, Head of Machine Learning Products at Cloudera.
“By lowering the barriers to innovation and differentiation with enterprise machine learning, Cloudera Machine Learning enables rapid onboarding and agile experimentation at scale for data science teams.”
The new machine learning service on the Cloudera Data Platform provides data scientists, data engineers and machine learning engineers with:
- Instant workspaces – deploy new machine learning workspaces for teams in a few clicks, with access to the project environments and resources they need for end-to-end machine learning.
- Rapid replication – provide democratised access to replicate data sets across hybrid and multi-cloud environments while maintaining enterprise data security and governance controls.
- Choose your own tools – provide data science teams with access to their favourite, open data science tools while preserving security and minimising administrative overhead.
- Elastic, auto-suspending resources – deliver the scale-out, heterogeneous computing resources data science teams need to get work done fast while maintaining adjustable guardrails that help IT easily manage and optimise infrastructure resources and costs.
- Comprehensive, cohesive user experience – data engineering, model training, experiment tracking, and deploying and managing production models all in one seamless environment, without switching or stitching workflows together with multiple tools.
- Portability and consistency – the liberty to move data and infrastructure anywhere without creating disconnected silos and without changing the consistent user experience that data science teams rely on for building robust workflows and processes for end-to-end ML.
Cloudera Machine Learning is fully integrated with the Cloudera Data Platform (CDP), including Cloudera Data Warehouse and Data Hub, allowing for the fast delivery of new multifunction analytics and machine learning in any cloud. This makes it possible for businesses to build, manage and scale intelligent applications fuelled by data anywhere –from the Edge to AI. Cloudera Machine Learning also fully capitalises on the Shared Data Experience (SDX) provided by CDP. Cloudera SDX provides consistent data security, governance and control across all multifunction analytics, for safe self-service access and discovery of data at enterprise scale.
Cloudera Machine Learning delivers a packaged experience for data engineering and machine learning workflows offered through a combination of consumption and per-user access pricing.
For more information on Cloudera Machine Learning on the Cloudera Data Platform, please click here.
Additional resources
Cloudera Machine Learning for CDP: Purpose Built for the AI-First Enterprise
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This press release contains forward-looking statements including, among other things, statements regarding the expected performance and benefits of Cloudera’s offerings. The words "believe," "may," "will," "plan," "expect," and similar expressions are intended to identify forward-looking statements. These forward-looking statements are subject to risks, uncertainties, and assumptions. If the risks materialize or assumptions prove incorrect, actual results could differ materially from the results implied by these forward-looking statements. Risks include, but are not limited to, risks described in our filings with the Securities and Exchange Commission (SEC), including our quarterly and yearly reports that we file with the SEC from time to time, which could cause actual results to vary from expectations. Cloudera assumes no obligation to, and does not currently intend to, update any such forward-looking statements after the date of this release.