Cloudera AI (formerly Cloudera Machine Learning) enables enterprise data science teams to collaborate across the full data lifecycle with immediate access to secure, trusted data pipelines, scalable compute resources, and preferred tools.

Cloudera AI covers the end-to-end machine learning workflow, enabling fully isolated and containerized workloads - including Python, R, and Spark-on-Kubernetes - for scale-out data engineering and machine learning with seamless distributed dependency management.

Cloudera Machine Learning covers the end-to-end machine learning workflow, enabling fully isolated and containerized workloads - including Python, R, and Spark-on-Kubernetes - for scale-out data engineering and machine learning with seamless distributed dependency management.

Cloudera AI is Cloudera’s cloud-native machine learning platform. Cloudera AI unifies self-service data science and data engineering in a single, portable service as part of an enterprise data cloud for multi-function analytics on data anywhere.

We'll discuss machine learning tools, platforms, and techniques, explore how Cloudera leverages ML in its platform, and dive into the key differences between machine learning and related fields like AI and deep learning.

Cloudera Machine Learning (CML), part of the Cloudera Data Platform (CDP), provides the solution, giving data science teams the required resources. This four-day course covers machine learning workflows and operations using CML.

2021年9月27日 · Cloudera Machine Learning’s new APIv2 provides all CML users with the ability to programmatically create, read, update and delete projects and workloads, including jobs, models and applications.

2020年7月21日 · CML is designed to be the platform on top of which data scientists can bring the Python, R, and Scala libraries and packages they need to run their workloads. This includes being able to leverage open source technologies, such as …

2019年11月25日 · Two pre-trained machine learning models (simple sklearn logistic regression models) are served by CML to be accessed by the application via API. As our focus is mainly on hosting the application using CML, let’s jump straight to that. Here’s a step-by-step instruction on how to leverage the “app hosting” capability of CML.

Cloudera Machine Learning offers a comprehensive solution for the full machine learning lifecycle and provides a trusted and efficient way to deploy complex models and support a diverse range of AI use cases.