The scikit-learn library is a collection of data mining algorithms, written in Python and using a. This library allows users to easily try different algorithms as well as utilize standard tools for doing effective testing and parameter searching. There are many algorithms and utilities in scikit-learn, including many of the commonly used algorithms in modern machine learning.
In this chapter, we focus on setting up a good framework for running data mining procedures. We will use this framework in later chapters, which focus on applications and techniques to use in those situations.
The key concepts introduced in this chapter are as follows:
- Estimators: This is to perform classification, clustering, and regression
- Transformers: This is to perform pre-processing and data alterations
- Pipelines: This is to put together your workflow into a replicable format
