Chapter 2:
Introduction to Scikit-Learn and Model Evaluation

Learning Objectives

By the end of this chapter, you will be able to:

• Explain the response variable
• Describe the implications of imbalanced data in binary classification
• Split data into training and testing sets
• Describe model fitting in scikit-learn
• Derive several metrics for binary classification
• Create an ROC curve and a precision-recall curve

This chapter will conclude the initial exploratory analysis and present new tools to perform model evaluation.