In this chapter, we will use the pandas, NumPy, SciPy, and Matplotlib Python libraries, all of which can be installed using the free Anaconda Python distribution. To do this, follow the instructions in the Technical requirements section of Chapter 1, Foreseeing Variable Problems when Building ML Models.
We will also use the open source Python library Featuretools, which can be installed using pip or conda. Follow the instructions in the following documentation: https://docs.featuretools.com/en/stable/getting_started/install.html.
Throughout the recipes in this chapter, we will work with a mock customer transaction dataset that comes with Featuretools and the Appliances energy prediction dataset, available in the UCI Machine Learning Repository: http://archive.ics.uci.edu/ml/datasets/Appliances+energy+prediction.
