Prophet Tutorial - UMD Classes -- Tutorials

This folder contains the setup for running Prophet time series forecasting tutorials within a containerized environment

Quick Start¶

From the root of the repository, change your directory to the Prophet tutorial folder:
```
> cd tutorials/tutorial_prophet
```
Build the Docker image:
```
> ./docker_build.sh
```
Launch Jupyter Lab inside the container:
```
> ./docker_jupyter.sh
```
Once ./docker_jupyter.sh is running, follow this sequence to explore the tutorials:
1. prophet.API.ipynb: Start here to learn the core Prophet API — basic usage, trend types, seasonality, holidays, external regressors, and cross-validation with small self-contained examples.
2. prophet.example.ipynb: Proceed to this notebook for a complete end-to-end forecasting workflow on a synthetic daily time series with controlled trend, seasonality, holiday, and autoregressive components.
For more information on the Docker build system refer to the Project template README