SageWorks: A Python WorkBench for creating and deploying AWS SageMaker Models

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  • License: MIT License (MIT)
  • Author: SuperCowPowers LLC
  • Tags SageMaker, Machine Learning, AWS, Python, Utilities
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Project description

Welcome to SageWorks

The SageWorks framework makes AWS® both easier to use and more powerful. SageWorks handles all the details around updating and managing a complex set of AWS Services. With a simple-to-use Python API and a beautiful set of web interfaces, SageWorks makes creating AWS ML pipelines a snap. It also dramatically improves both the usability and visibility across the entire spectrum of services: Glue Job, Athena, Feature Store, Models, and Endpoints, SageWorks makes it easy to build production ready, AWS powered, machine learning pipelines.

sageworks_new_light

Full AWS ML OverView

  • Health Monitoring 🟢
  • Dynamic Updates
  • High Level Summary

Drill-Down Views

  • Incoming Data
  • Glue Jobs
  • DataSources
  • FeatureSets
  • Models
  • Endpoints

sageworks_new_light

SageWorks Documentation

We have detailed documentation on the SageWprks Python API here: SageWorks Documentation. The documentation contains examples from souce code in this repository under the examples/ directory. For a full code listing of any example please visit our SageWorks Examples

Contributions

If you'd like to contribute to the SageWorks project, you're more than welcome. All contributions will fall under the existing project license. If you are interested in contributing or have questions please feel free to contact us at sageworks@supercowpowers.com.

SageWorks Beta Testers Wanted

Our experienced team can provide development and consulting services to help you effectively use Amazon’s Machine Learning services within your organization.

The popularity of cloud based Machine Learning services is booming. The problem many companies face is how that capability gets effectively used and harnessed to drive real business decisions and provide concrete value for their organization.

Using SageWorks will minimize the time and manpower needed to incorporate AWS ML into your organization. If your company would like to be a SageWorks Beta Tester, contact us at sageworks@supercowpowers.com.

Open Source Tools for Documentation

If you like the documentation it is based on these awesome open source projects, please give them your support:

® Amazon Web Services, AWS, the Powered by AWS logo, are trademarks of Amazon.com, Inc. or its affiliates.

Project details

Verified details

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Maintainers
Avatar for briford from gravatar.com briford

Unverified details

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Meta
  • License: MIT License (MIT)
  • Author: SuperCowPowers LLC
  • Tags SageMaker, Machine Learning, AWS, Python, Utilities
Classifiers

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