Deliver more ML
use cases, faster

Accelerate the ML lifecycle with one platform for building, deploying, serving, and operating models at scale.


Experience Machine Learning on Cloudera Data Platform (CDP) for yourself

With ML on CDP, you can deliver more use cases, faster. Purpose-built tooling for the full data lifecycle enables immediate access to enterprise data pipelines, scalable compute resources, and any library or IDE of your choice. Streamline the process of moving analytic workloads into production and intelligently manage ML use cases across the business at scale.
Any AI Use Case
Intuitive self-service
Rapid Model deployment
Real-time collaboration
Performance and scale
Model governance
Jumpstart your project

Accelerate your ML projects with Applied Machine Learning Prototypes (AMPs)

AMPs are complete ML projects that help enterprises deliver ML use cases much faster than before. With open code, pre-canned models, and business applications out of the box, AMPs help your business realize ROI from ML at greater scale.
Deep Learning for Anomaly Detection

Apply modern, deep learning techniques for anomaly detection to identify network intrusions.

Churn Modeling with scikit-learn

Build a scikit-learn model to predict churn using customer telco data

Object Detection Inference Visualized

Interact with a blog-style Streamlit application to visually unpack the inference workflow of a modern, single-stage object detector.

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Deep Learning for Image Analysis

Build a semantic search application with deep learning models.

Few-Shot Text Classification

Perform topic classification on news articles in several limited-labeled data regimes.

Deep Learning For Question Answering

Explore an emerging NLP capability with WikiQA, an automated question answering system built on top of Wikipedia.

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Open tooling

Power enterprise ML with the freedom of open source. Natively use the frameworks, IDEs, libraries, and ML tools you prefer.

Use Cases

Managing the ML lifecycle with one place to build, deploy, serve, and operate many models.

Deliver ML models that solve problems and spark industry-wide innovation today and into the future.

Easily develop, deploy, and sustain ML models that power predictive analytic use cases across your business. No matter the business challenge, Cloudera lets you accelerate the full ML lifecycle—from data pipelines, to model building, and business impact—at scale from a single pane of glass.


Analyzing breast cancer probability using a logistic regression model

By building a logistic regression model with your hospital's breast cancer dataset using Python on CML, you can deploy an ML model that predicts whether a breast lump is benign or malignant.


Validating jet engine models

By using engine data as an input for a regression model, you can build an ML model for alerting an airline for when an engine is likely to pass a certain threshold of remaining useful in life.


Building a sentiment analysis application

By pulling in social media datasets via APIs, you can build and train ML models to present visualized sentiment scores for insights into brand messaging and reputation.


Resources and guides to get you started with ML on CDP  

Cloudera Data Platform streamlines enterprise ML—but Cloudera's documentation and guides will never cut corners. We offer a robust library of resources to show you what's possible with CML and other CDP experiences, step by step.

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