Project Structure for MLflow integrated ML Projects
This cli tool generates the following directory structure for quickstart ML projects
installaton:
pip install aihubcli
example use:
aihubcli create mytestproject
It generates the project with following structure
Project
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+--- Input
| |
| +--- raw Raw data here
| |
| +--- interim Any intermediate data, to pause and continue experiments
| |
| +--- processed Processed data ready for ML pipeline
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+--- output
| |
| +--- models Model pickle or model weights stored here
| |
| +--- artifacts Serialized artifacts like LabelEncoder, Vectorizer etc
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| +--- images All plots and visualizations goes here
| |
| +--- Results If the results needs to be stored for review, save here
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+--- notebooks All notebooks and experiments resides here
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+--- src Final program, with training and prediction pipeline
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README.md Description and instruction about the project
MLProject MLflow project file. If you want to use this directory as MLflow project
Requirements.txt python dependencies
Config.yml configuration key values in yaml format
