Before running any notebook or flask app, please put the raw data into the data/raw/ folder
Raw data could be found here: https://www.kaggle.com/c/competitive-data-science-predict-future-sales/data

To use the flask app:

• Put raw data into the data/raw/ folder

• Initiate the pipenv environment and install necessary packages:

  pipenv shell
  pipenv install
  

• Start the flask endpoint that serves the trained model:

  python src/endpoint.py
  

  URL query example:

  http://localhost:8000/?shop_id=5&shop_id=1&shop_id=10&item_id=11&item_id=8&item_id=44
  

Project structure:

• data: raw and processed data used for training and inference
• models: models saved during experiments
• src: classes, settings and utilities used in modelling and data transformation
• notebooks:
  • EDA: short data exploration
  • ETL: sandbox notebook for development and testing of feature engineering and cross validation
  • modelling: sandbox for modelling experiments
  • kaggle_submission: notebook to generate kaggle submissions