Technical requirements
In this chapter, we will use the following Python libraries and versions to perform feature engineering on different datasets.
azureml-sdk 1.34.0
azureml-widgets 1.34.0
azureml-dataprep 2.20.0
pandas 1.3.2
numpy 1.19.5
scikit-learn 0.24.2
seaborn 0.11.2
plotly 5.3.1
umap_learn 0.5.1
statsmodels 0.13.0
missingno 0.5.0
Similar to previous chapters, you can execute this code using either a local Python interpreter or a notebook environment hosted in Azure Machine Learning.
All code examples in this chapter can be found in the GitHub repository for this book: https://github.com/PacktPublishing/Mastering-Azure-Machine-Learning-Second-Edition/tree/main/chapter06.