This chapter introduces you to machine learning and building models using the sklearn
library.
We will be working in the following notebooks:
planets_ml.ipynb
: shows how to build clustering and linear regression models using the planet datapreprocessing.ipynb
: walks through various preprocessing techniquesred_wine.ipynb
: discusses how to build a classification model to predict red wine qualitywine.ipynb
: walks through creating a classification model to predict wine type
Note that the planets_data_collection.ipynb
notebook contains the code used to collect the planet data.
All the datasets necessary for the aforementioned notebooks, along with information on them, can be found in the data/
directory. The end-of-chapter exercises will also use this data to practice building ML models with scikit-learn; solutions to these exercises can be found in the repository's solutions/ch_09/
directory.