Package for automated sales forecasting. For conceptual understanding, read the paper here. https://medium.com/towards-data-science/5-machine-learning-techniques-for-sales-forecasting-598e4984b109

This package is a refactored version of original code found here: https://github.com/mollyryanruby/sales_forecasting To see the original code, click through the link above.

The easiest way to learn how to deploy the auto_forecast package is to step through the code in the example notebook found at auto_forecast/example/example_notebook.ipynb

• Time series EDA
• Pre-processing to generate supervised time series data
• Modeling
  • Linear Regression
  • Random Forest
  • XGBoost
  • ARIMA
  • Long Short Term Memory (LSTM)