Time Series Forecasting with ARIMA
This tutorial demonstrates how to implement the models and forecasting discussed in this unit. Since we are using Google Colab, you can jump to Step 2 to begin this programming example. Upon completing this tutorial, you should be able to construct models, make forecasts and validate forecasts given a time series data set.
Prerequisites
This guide will cover how to do time-series analysis on either a local desktop or a remote server. Working with large datasets can be memory intensive, so in either case, the computer will need at least 2GB of memory to perform some of the calculations in this guide.
To make the most of this tutorial, some familiarity with time series and statistics can be helpful.
For this tutorial, we'll be using Jupyter Notebook to work with the data.