SageWorks: A Python WorkBench for creating and deploying AWS SageMaker Models
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.
Full AWS ML OverView
- Health Monitoring 🟢
- Dynamic Updates
- High Level Summary
Drill-Down Views
- Incoming Data
- Glue Jobs
- DataSources
- FeatureSets
- Models
- Endpoints
Private SaaS Architecture
Secure your Data, Empower your ML Pipelines
SageWorks is architected as a Private SaaS. This hybrid architecture is the ultimate solution for businesses that prioritize data control and security. SageWorks deploys as an AWS Stack within your own cloud environment, ensuring compliance with stringent corporate and regulatory standards. It offers the flexibility to tailor solutions to your specific business needs through our comprehensive plugin support, both components and full web interfaces. By using SageWorks, you maintain absolute control over your data while benefiting from the power, security, and scalability of AWS cloud services. SageWorks Private SaaS Architecture
API Installation
-
pip install sageworksInstalls SageWorks -
sageworksRuns the SageWorks REPL/Initial Setup
For the full instructions for connecting your AWS Account see:
- Initial Setup/Config: Initial Setup
- One time AWS Onboarding: AWS Setup
SageWorks Documentation
SageWorks Documentation: The documentation contains examples from the SageWorks source code in this repository under the examples/ directory. For a full code listing of any example please visit our SageWorks Examples
SageWorks Beta Program
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.
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.
® Amazon Web Services, AWS, the Powered by AWS logo, are trademarks of Amazon.com, Inc. or its affiliates
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