SuperCowPowers/workbench
Workbench: An easy to use Python API for creating and deploying AWS SageMaker Models
This tool helps scientists and researchers in drug discovery quickly create, manage, and deploy machine learning models for predicting molecular properties (ADMET) on AWS. It takes molecular structures as input and outputs predictions for their absorption, distribution, metabolism, excretion, and toxicity. It's designed for chemists and computational biologists who need to run and monitor predictive models without deep AWS expertise.
Used by 1 other package. Available on PyPI.
Use this if you are a cheminformatician, medicinal chemist, or computational biologist who wants to build and deploy robust ADMET prediction models using Chemprop and AWS, while retaining full control over your data.
Not ideal if you are looking for a general-purpose machine learning platform outside of the ADMET domain or if you prefer not to use AWS infrastructure.
Stars
50
Forks
5
Language
Python
License
MIT
Category
Last pushed
Mar 12, 2026
Commits (30d)
0
Dependencies
20
Reverse dependents
1
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