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The purpose of this live-coding series is to take a simple model trained in Jupyter notebook and refactor it into a nice Python project. We demonstrate how good coding practices can be applied in Deep Learning domain. These series are non-exhaustive and serve as an entrypoint for those who are curious about `MLOps` and `PytorchLightning`. |
- Follow instructions
to install Poetry:
# Unix/MacOs installation curl -sSL https://install.python-poetry.org | python3 -
- Check that poetry was installed successfully:
poetry --version
- Setup workspace:
make setup_ws
- Setup ClearML:
clearml-init
- Migrate dataset to your ClearML workspace:
make migrate_dataset
- (Optional) Configure and run Jupyter lab:
make jupyterlab_start
make run_training- PytorchLightning + Hydra - a very nice repo template
- ClearML intro - showcase of main ClearML features