Data Science with Python

Chapter 5

Mastering Structured Data

Learning Objectives

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

• Work with structured data to create highly accurate models
• Use the XGBoost library to train boosting models
• Use the Keras library to train neural network models
• Fine-tune model parameters to get the best accuracy
• Use cross-validation
• Save and load your trained models

This chapter will cover the basics on how to create highly accurate structured data models.

Introduction

There are two main types of data, structured and unstructured. Structured data refers to data that has a defined format and is usually shaped as a table, such as data stored in an Excel sheet or a relational database. Unstructured data does not have a predefined schema. ...