Data Science - Time Series Forecasting with Facebook Prophet in Python - How Does Prophet Work?

The video tutorial provides an overview of Facebook Prophet, a time series forecasting tool optimized for business applications. It explains the model's components, including trend, seasonality, and holiday effects, and highlights its ability to handle outliers and missing data. The tutorial also covers the Bayesian approach used in Prophet, allowing for client involvement in the modeling process. Key features such as piecewise linear and logistic growth trends, as well as the use of Fourier series for seasonality, are discussed.

How does Facebook Profit deal with outliers and missing data?

What are the two methods used by Facebook Profit to model trends?

What is the role of Bayesian methods in the Facebook Profit model?