Forecast Model Tuning with Additional Regressors in Prophet

I’m going to share my experiment results with Prophet additional regressors. My goal was to check how extra regressor would weight on forecast calculated by Prophet.

Using dataset from Kaggle — Bike Sharing in Washington D.C. Dataset. Data comes with a number for bike rentals per day and weather conditions. I have created and compared three models:

1. Time series Prophet model with date and number of bike rentals
2. A model with additional regressor —weather temperature
3. A model with additional regressor s— weather temperature and state (raining, sunny, etc.)

We should see the effect of regressor and compare these three models.

Read more in my Towards Data Science post.

Serving Prophet Model with Flask — Predicting Future

The solution to demonstrate how to serve Prophet model API on the Web with Flask. Prophet — Open-Source Python library developed by Facebook to predict time series data.

An accurate forecast and future prediction are crucial almost for any business. This is an obvious thing and it doesn’t need explanation. There is a concept of time series data, this data is ordered by date and typically each date is assigned with one or more values specific to that date. Machine Learning powered models could generate forecasts based on time series data. Such forecasts could be an important source of information for business decisions.

Read more in my Towards Data Science post.