madewithml / Boilerplate
Licence: mit
🍪 ML application template to create API services around your ML code.
Stars: ✭ 112
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python
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ML Application Template
An application template to wrap your machine learning code as a FAST RESTful API, complete with Dockerfiles, TensorBoard, etc. Check out these simple projects for examples of how this template can be leveraged. → 
TensorFlow or 
PyTorch
Set Up
pip install cookiecutter invoke requests
cookiecutter gh:madewithml/ml-app-template
Steps
- Update
requirements.txtas needed. - Add ML functionality inside
{{ cookiecutter.package_name }}. - Add unit tests in
testsas you develop. - Add API functionality inside
app.py. - Complete
README.mdwith the appropriate details. - Ensure that the
Dockerfileis updated. - Update
.gitignorebefore committing to git.
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