This chapter will cover using Scikit-learn to implement machine learning models using techniques such as
Feature engineering
Resampling methods
Model evaluation methods
Pipelines for streamlining machine learning workflows
Techniques for model tuning
Feature Engineering
Feature engineering is the process of systematically choosing the set of features in the dataset that are useful and relevant to the learning problem. It is often the case that irrelevant features negatively affect the performance of the ...
