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Makefile
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.PHONY: clean dirs virtualenv lint requirements push pull
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#################################################################################
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# GLOBALS #
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pull:
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dvc pull
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##
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dvc repro
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#################################################################################
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# PROJECT RULES #
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.PHONY: clean dirs virtualenv lint requirements push pull run
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#################################################################################
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# GLOBALS #
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pull:
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dvc pull
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## run the DVC pipeline - recompute any modified outputs such as processed data or trained models
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run:
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dvc repro dvc.yaml
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#################################################################################
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# PROJECT RULES #
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README.md
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@@ -10,7 +10,7 @@ Instructions
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1. *Optional:* Run `make virtualenv` to create a python virtual environment. Skip if using conda or some other env manager.
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1. Run `source env/bin/activate` to activate the virtualenv.
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1. Run `make requirements` to install required python packages.
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1. Process your data, train and evaluate your model using `
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1. When you're happy with the result, commit files (including .dvc files) to git.
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Project Organization
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1. *Optional:* Run `make virtualenv` to create a python virtual environment. Skip if using conda or some other env manager.
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1. Run `source env/bin/activate` to activate the virtualenv.
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1. Run `make requirements` to install required python packages.
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1. Process your data, train and evaluate your model using `make run`
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1. When you're happy with the result, commit files (including .dvc files) to git.
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Project Organization
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