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Machine learning and process automation
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README.md Update README.md Mar 26, 2019
credentials.json ML DB integration Feb 11, 2019
diabetes-model.pkl Flask endpoint Mar 26, 2019
diabetes_redsamurai_db.ipynb Fix Mar 31, 2019
diabetes_redsamurai_endpoint_db.ipynb Flask endpoint Mar 26, 2019
diabetes_redsamurai_endpoint_db.py Flask endpoint Mar 26, 2019
invoice-automation-d1.ipynb Data transformation for ML training Nov 29, 2018
invoice-automation-d2.ipynb
invoice-risk-model-local.ipynb On premise xgboost Jan 8, 2019
invoice_data_adjusted.csv Initial commit Nov 7, 2018
invoice_data_prog_processed.csv Data transformation for ML training Nov 29, 2018

README.md

Process automation with Machine Learning.

  1. invoice-automation-d1.ipynb - date is split into multiple columns
  2. invoice-automation-d2.ipynb - instead of splitting date, using date difference in days
  3. invoice-risk-model-local.ipynb - step by step notebook to run xgboost on premise
  4. diabetes_redsamurai_db.ipynb - notebook which demonstrates how to fetch training data directly from DB, prepare train/test datasets and run training with XGBoost
  5. diabetes_redsamurai_endpoint_db.ipynb - notebook which demonstrates how to use Flask to expose XGBoost ML model

Author: Andrejus Baranovskis, Red Samurai Consulting (http://redsamuraiconsulting.com)

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