Experimenting with Facebook’s Prophet library!
Facebook’s Data Science teams, as well as operational teams, are often faced with coming with forecasts for infrastructure peaks/troughs etc. For example, if 1 million users suddenly needed to look at cat memes. This means good infrastructure planning is needed!
To make life easier and come up with quick forecasts, Facebook developed Prophet - it is designed to operate on daily basis and factors in holiday effects, seasonality etc. The library allows powerful forecasting without a significant amount of statistical tweaking, such as required in more heavy methods, such as ARIMA models.
It’s basically forecasting out of the box for time-series data- and its free!
Fulfilling out Prophecy using Prophet
Using Facebook’s open-sourced forecasting library, we are able to do lightweight forecasting to get powerful results!
So what did we find?
Prophet comes with a lot of out of the box libraries that let you see your time-series data. In this case, I picked Brisbane weather data and played around with the temperature dataset from 1999 to 2019.
The forecasting model I created eventually came up with this prediction, with the blue shaded around indicating the confidence interval and black dots indicating actual temperature reads:
Finding the unexpected!
In the Exploratory Data Analysis of the Brisbane weather forecasts, I also picked up a few interesting tidbits!
What do the graphs show? Well interesting:
-
Global Warming! Brisbane is getting hotter, with the average temperature gradually going up over time!
-
Cold Thursdays! Thursday seems to be on average the coldest day of the week!, while Saturday seems to be on average the hottest
-
Chilly Julys! Being Southern hemisphere peeps, Brisbane’s July is the coldest month and February being the hottest!
See the details in my Kaggle notebook!
In my Kaggle Notebook, I walk through how I did the preprocessing, EDA and training and cross-validation of the weather datasets!