Thanks for the original contribution from the artical Version your machine learning models with Sacred and Managing Machine Learning projects.
This example reorganize the project monchewharry/ML-manage-tfexample into general project structure as suggested by the mentioned credit above. The project running is similar, just by the following and read the printted hints to start omniboard
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python run.py
- add hyperparameter tune (no duplicate experiment control)
- add unittest
- add docker
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├── README.md
├── run.py
├── src
│ ├── config.py
│ ├── data_processing
│ │ └── data_loader.py
│ ├── inference.py
│ ├── models
│ │ └── model.py
│ ├── train.py
│ ├── utils
│ └── visualization
│ └── explore.py
└── tests
├── data
│ └── test-set.py
├── integration
│ └── test_model.py
└── unit
└── test_data_loader.py