Overview
The freedom data science teams need delivered by a cloud-native service that works for IT.
CDP Machine Learning enables enterprise data science teams to collaborate across the full data lifecycle with immediate access to enterprise data pipelines, scalable compute resources, and access to preferred tools. Streamline the process of getting analytic workloads into production and intelligently manage machine learning use cases across the business at scale.
CDP Machine Learning optimizes ML workflows across your business with native and robust tools for deploying, serving, and monitoring models. With extended SDX for models, govern and automate model cataloging and then seamlessly move results to collaborate across CDP experiences including Data Warehouse and Operational Database.
For data scientists
Optimize the ML data lifecycle and operationalize machine learning models across the business with transparent and repeatable workflows that work for everyone.
Experience the tools for yourself
For IT leaders
Give your data science teams the resources they need to experiment, iterate, and impact the business anywhere, without compromising agility, security, or governance.
Use cases
Jumpstart AI Use Cases
Quickly experiment, iterate, and tune
Share insights everywhere
Cost-effectively operate models
Jumpstart ML use cases
Move the starting line for ML projects with applied machine learning prototypes in CML.
Applied ML prototypes (AMPs) are complete ML projects that help kick-start specific enterprise AI use cases. With open code, pre-canned models, and complete business applications out of the box, AMPs help your business realize ROI from AI faster and at greater scale.
Quickly experiment, iterate, and tune
Experiment and tune your ML models securely.
Experimentation is key when developing and deploying machine learning models across your enterprise. With experiments in CDP Machine Learning, enable your data science teams to test various approaches and perform hyperparameter tuning to best serve your business.
Share insights everywhere
Deliver actionable predictive dashboards across your business quickly and easily.
Data scientists and stakeholders across the ML lifecycle can build self-service drag-and-drop visualizations that enable everyone to ask predictive questions directly from machine learning models deployed and served in Cloudera Machine Learning.
Cost-effectively operate models
The complete toolset for production ML at scale.
Deploy models into production with a few clicks and manage all of your production environment from a single pane of glass. Leverage CDP Shared Data Experience (SDX) for models, monitor prediction metrics, ground truth production applications, and quickly identify model drift before it impacts your business.
Deploy machine learning workspaces in a few clicks, giving data science teams access to the project environments and automatically elastic compute resources they need for end-to-end ML without waiting.
With CDP Machine Learning, administrators and data science teams have full visibility from data source to production environment—enabling transparent workflows and easy collaboration across teams securely.
Cloudera Machine Learning offers both a robust built-in workbench and the flexibility to natively use favorite tools such as Jupyter Notebooks and RStudio while preserving security, efficiency, and scalability without administrative overhead.
Always achieve the optimal outcome with advanced experimentation capabilities for hyperparameter tuning and multi-model testing for production workloads.
Cloudera Machine Learning’s MLOps capability enables one-click model deployment, model cataloging, and granular prediction monitoring to keep models secure and accurate across production environments.
Deliver insights with a consistent and easy-to-use experience, featuring intuitive and accessible drag-and-drop dashboards and custom application creation.
Deployment options
Deploy CDP Machine Learning anywhere with a cloud-native, portable, and consistent experience everywhere.
CDP Public Cloud
- Multi-cloud ready: Don’t get locked into a single cloud provider. Power your AI initiatives holistically with data from anywhere
- Scalable: Leverage scalable and auto-suspending compute resources that you only pay for while in use
- Full lifecycle integration: Seamlessly and securely share workloads and outputs across CDP experiences including Cloudera Data Engineering and Data Warehouse
CDP Private Cloud
- Cost-effective: Optimized resource utilization from disaggregated storage affords cost-efficiencies across the cluster
- Optimized performance: Meet your SLAs every time with workload isolation and multi-tenancy for critical workloads
- Collaborate effectively: Securely share workloads, data, and results across teams at every stage of the data lifecycle
For the Private Cloud Base form factor of CDP Machine Learning, please see Cloudera Data Science Workbench.
Get started
CDP weekly demo
Join Cloudera technical experts for a weekly demo and live Q&A. Learn how to connect the lifecycle of your data to power AI use cases.
Discover CDP video tour
Look under the hood with a video tour of CDP and discover how secure and optimized ML workflows can better serve your business.
CDP technical resources
Save time with technical information and resources to help you develop your skills and gain knowledge about Cloudera Machine Learning.
Free training
Access on-demand training to get up to speed with CML on CDP to enable streamlined, self-service machine learning across the enterprise.
Pricing
Evaluate pricing, billing terms, licensing details, and hourly rates as well as estimate costs with handy calculators.
Product documentation
Get started on the right foot with resource planning, product configuration, and everything you need for ML best practices.
