Data Science Projects with Python

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.

Introduction

The first chapter got you started with some basic Python, and then progressed to equipping you with tools for data exploration. Specifically, we performed operations such as loading the dataset and verifying data ...