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Cloudera Machine Learning

End-to-end services to deliver machine learning at scale, from the leading services provider for Cloudera.

We are honored to be awarded Cloudera's 2020 North American Partner of the Year!

Cloudera Partner of the Year phData 2020

Machine learning is hard — delivering models at-scale is even harder. Data scientists often lack the engineering expertise to ensure the models they design will be performant and scalable for a given infrastructure use case; meanwhile, traditional software engineers may not be familiar with the unique combination of tools and languages that ML applications typically rely on.

Cloudera Machine Learning from phData gets your models into production. As the leading specialist provider of data engineering and ML services for Cloudera, our data scientists know engineering, and our engineers know data. From ideation to post-implementation support, we support you across the entire lifecycle of a machine learning project.

Cloudera Machine Learning Offerings

Choose the right combination of support and Cloudera platform expertise to fit your needs across the full data product lifecycle:

Data Scientist

Data
Science

Develop solutions for your businesses' toughest data problems. Tap into our data science team to help unlock the hidden potential of your data. Assess, model, train, and optimize to give you confidence in each solution.

phData Data Engineering

Machine Learning Engineering

Our team of multidisciplinary ML engineers and architects helps you harden, scale, and integrate ML applications to deliver real value — defining MLOps processes and infrastructure patterns for repeatable future success.

Data Science Team

Managed Machine
Learning

Deploy and manage your ML models, with 24x7 monitoring and alerting, as well as proactive remediation (such as model refitting) to rectify problems before they impact the business.

We accelerate migrations to Cloudera CDP.

Machine learning that delivers

Discovering all new ways
to put your data to work

From use-case exploration to data identification and acquisition, we help you identify ML opportunities, obstacles, and goals from data discovery to model training. We provide the engineering perspective to help ensure a measurable and successful delivery.

Machine learning that
delivers at scale

One-off solutions are not the path to ML success. Our multidisciplinary ML engineers have the skills to implement the proper infrastructure and processes you need to build, optimize, and scale production-ready ML applications that integrate with key business systems.

Accuracy and operational
confidence

Degraded models lead to bad predictions, which lead to risk and financial damage. We help ensure models are properly validated and tested, then work to detect issues, ensure visibility, and proactively identify and refit drifting models before they harm the business.

Keeping your most valuable
resources productive

Keep data scientists productive with specialized support for machine learning tools and platforms. We manage machine learning tools, manage stability and multi-tenancy, deal with the different dependency stacks, and manage complex and unsupported open source tooling. With our experts on hand, data scientists are free to focus on solving business problems.

Why phData for Machine Learning on Cloudera?

ML expertise meets Cloudera know-how

At phData, engineering is our DNA. We hire data scientists with a practical understanding of how to build and deliver models that hold up in production. As the leading specialist provider for ML and data engineering on Cloudera, we bring deep platform-specific expertise to help you:
  • Break down data silos on the Cloudera platform.
  • Develop, train, experiment, and deploy models following phData best practices on the Cloudera platform.
  • Leverage Cloudera’s native distributed computing capabilities to scale your project as needed.
Machine Learning phData

Support and expertise across the full ML lifecycle

We bring the right people with the right skills at each stage of the full machine learning lifecycle
— helping you implement repeatable processes and frameworks at every step to iterate and deliver models faster.

From ideation to model training to deployment to post-implementation support, we help ensure your Cloudera-based ML projects deliver value — whether its integrating with Cloudera Data Science Workbench to help with testing, experiment tracking and model selection, or integrating platform-specific best practices for deploying models on the Cloudera platform.

A vigilant, systematic approach to ML security

With experience implementing successful projects in highly regulated industries, we understand how to help your ML initiatives deliver value without sacrificing security. We assist with model authorization, model cataloging, data-set and feature cataloging, model interpretability, audit, and monitoring to ensure your ML projects adhere to appropriate legal, ethical, and regulatory constraints. Our emphasis on automation, repeatability, data transparency, and process standardization minimizes human error — and therefore minimizes risk. If needed, we can work with Cloudera Atlas and Navigator to centralize your regulatory and lineage requirements all in one location.

Ready to learn more about phdata Cloudera Machine Learning Services? Let's chat.