Forecasting Best Practices, from Microsoft

Microsoft has released a GitHub repository to share , and then operationalize the forecasts as a web service.

The ). The forecasting techniques vary (mean forecasting with interpolation, ARIMA, exponential smoothing, and additive models), but all make extensive use of the ". The forecasting methods themselves are explained in detail in the book (readable online)

You can try out the examples yourself by cloning the repository and knitting the RMarkdown files in R. If you have git installed, a quick and easy way to do this in with RStudio. Choose File > New Project > Version Control > Git, and enter

Open each .Rmd file in turn, accept the prompt to install packages, and click the Knit button to generate the document. The computations can take a while (particularly the Prophet Models example), but if you have a multi-core machine the notebooks do use the in my fork so I could link to them directly below: