Time-series Forecasting Using Facebook Prophet Package

Forecasting is a technique that is used for a variety of different purposes and situations such as sales forecasting, operational and budget planning etc. Similarly there are a variety of different techniques such as moving averages, smoothening, ARIMA etc to statistically make a forecast.

In this article we will talk about an open source package called “Prophet” from Facebook which takes away the complexity of other techniques without compromising on accuracy of the forecast. The guiding principle of this approach is General Additive Models (GAMs). More on which can be found over here.

Let’s look at an example of how to deploy Prophet in Python.

 

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Cheers!

2 thoughts on “Time-series Forecasting Using Facebook Prophet Package

  1. Pingback: Learn Data Science using Python Step by Step | RP's Blog on data science

  2. Pingback: Recurrent Neural Network (RNN) in Python | RP's Blog on data science

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