This chapter will expose us to the vernacular of machine learning and common tasks that machine learning can be used to solve. Afterwards we will learn how we can prepare our data for use in machine learning models. We have discussed data cleaning already, but only for human consumption—machine learning models require different preprocessing (cleaning) techniques. There are quite a few nuances here, so we will take our time with this topic and discuss how we can use scikit-learn to build preprocessing pipelines that streamline this procedure, since our models will only be as good as the data they are trained on.
Next, we will walk through how we can use scikit-learn to build a model and evaluate its performance. Scikit-learn has a very user-friendly API, so once we know how to build one, we can build any number of them. We...
