ML Hackathon 2022. Showcase your skills by developing an ML prototype for prizes

Deliver more machine learning use cases, faster

Accelerate machine learning projects with pre-built applied machine learning prototypes.

AMPs diagram of Infographic
Overview

Cloudera’s Applied Machine Learning Prototypes (AMPs) move data science projects from concept to reality with pre-built solutions that provide single-click access to proven machine learning applications that address common business use cases.  

  • Fast:  Provide starting point to build, deploy and monitor business-ready machine learning applications. 
  • Customizable:  Complete machine learning framework enables models to be trained using customized datasets making it easy to go from idea to production. 
  • Reliable:  Applied best practices and thorough testing and review with Cloudera Fast Forward Labs and our hardware partners ensure our AMPs deliver trusted, reliable results.

 

Applied Machine Learning Prototypes (AMPs) are changing the future of machine learning.

AMPs are fully-developed prototypes based on common use cases that have built-in best practices and rigorously tested code with the ability to retrain or create applications unique to your organization.  By shortening the time it takes to get from A to Z by starting at Y, see how AMPs will forever change how your ML projects are built and delivered.

Use cases

An easier way to deploy machine learning use cases for faster delivery, greater scale and higher success rate.

Applied Machine Learning Prototypes (AMPs) change the way machine learning projects are built and delivered.  These fully-developed prototypes provide a head start to solving common industry challenges.


  • Churn modeling
  • Deep learning for anomaly detection
  • Continuous model monitoring

Churn modeling



Proactively identify customers that are attrition risks with churn modeling applied machine learning prototype.

Enterprises across telecommunications, financial services and other sectors rely on strong customer retention. Cloudera’s Churn Modeling off-the-shelf Applied Machine Learning Prototype helps data scientists identify high attrition risk customers from which companies can devise strategies to reduce churn and drive customer lifetime value.

Ebook thumbnail

Taking machine learning from research to results

Learn about Applied Machine Learning Prototypes (AMPs) and how these fully developed prototypes offer data scientists a running start to bring machine learning applications from concept to reality. AMPs provide high-quality, professionally developed code and the ability to learn from and modify prototypes for faster results.

Deep learning for anomaly detection



Deliver valuable insights on what should and should not be with with deep learning for anomaly detection applied machine learning prototype.    

Fraud detection, medical diagnosis and predictive maintenance all rely on identifying outliers and anomalies in very large datasets.Cloudera’s Deep Learning for Anomaly Detection off-the-shelf Applied Machine Learning Prototype allows data scientists to get models into production and deliver valuable insights faster.

Ebook thumbnail

Taking machine learning from research to results

Learn about Applied Machine Learning Prototypes (AMPs) and how these fully developed prototypes offer data scientists a running start to bring machine learning applications from concept to reality. AMPs provide high-quality, professionally developed code and the ability to learn from and modify prototypes for faster results.

Continuous model monitoring



Ensure production models continue to provide accurate information over time.     


Even the best machine learning models are subject to drift in production environments putting enterprise forecasts, product safety and defect identification capabilities at risk. Cloudera’s Continuous model monitoring off-the-shelf Applied Machine Learning Prototype adds functionality that helps data scientists ensure data and numerical drift don’t compromise models’s accuracy and reliability.
 

Ebook thumbnail

Taking machine learning from research to results

Learn about Applied Machine Learning Prototypes (AMPs) and how these fully developed prototypes offer data scientists a running start to bring machine learning applications from concept to reality. AMPs provide high-quality, professionally developed code and the ability to learn from and modify prototypes for faster results.

Jumpstart your project

Power your machine learning projects with a single click

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.

Show less
Documentation

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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