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b6e8b9ccca
* add pipeline tuner component and dependencies. * clean code. * do not need force rerun. * replace the resources. * update metrics retrieving. * Update test/pipeline_tuning_example/requirements.txt * Update test/pipeline_tuning_example/train/env.yaml * Update test/pipeline_tuning_example/tuner/env.yaml * Update test/pipeline_tuning_example/tuner/tuner_func.py * Update test/pipeline_tuning_example/data_prep/env.yaml * fix issues found by lint with flake8. * add documentation * add data. * do not need AML resource for local run. * AML -> AzureML * clean code. * Update website/docs/Examples/Tune-AzureML pipeline.md * rename and add pip install. * update figure name. * align docs with code. * remove extra line.
14 lines
248 B
YAML
14 lines
248 B
YAML
name: data-prep-env
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channels:
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- conda-forge
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dependencies:
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- python=3.8
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- numpy=1.21.2
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- pip=21.2.4
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- scikit-learn=0.24.2
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- scipy=1.7.1
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- pandas>=1.1,<1.2
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- pip:
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- lightgbm==3.3.2
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- mlflow==1.26.1
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- azureml-mlflow==1.42.0 |