Book Image

The Data Science Workshop - Second Edition

By : Anthony So, Thomas V. Joseph, Robert Thas John, Andrew Worsley, Dr. Samuel Asare
5 (1)
Book Image

The Data Science Workshop - Second Edition

5 (1)
By: Anthony So, Thomas V. Joseph, Robert Thas John, Andrew Worsley, Dr. Samuel Asare

Overview of this book

Where there’s data, there’s insight. With so much data being generated, there is immense scope to extract meaningful information that’ll boost business productivity and profitability. By learning to convert raw data into game-changing insights, you’ll open new career paths and opportunities. The Data Science Workshop begins by introducing different types of projects and showing you how to incorporate machine learning algorithms in them. You’ll learn to select a relevant metric and even assess the performance of your model. To tune the hyperparameters of an algorithm and improve its accuracy, you’ll get hands-on with approaches such as grid search and random search. Next, you’ll learn dimensionality reduction techniques to easily handle many variables at once, before exploring how to use model ensembling techniques and create new features to enhance model performance. In a bid to help you automatically create new features that improve your model, the book demonstrates how to use the automated feature engineering tool. You’ll also understand how to use the orchestration and scheduling workflow to deploy machine learning models in batch. By the end of this book, you’ll have the skills to start working on data science projects confidently. By the end of this book, you’ll have the skills to start working on data science projects confidently.
Table of Contents (16 chapters)
Preface
12
12. Feature Engineering

Python for Data Science

Python offers an incredible number of packages for data science. A package is a collection of prebuilt functions and classes shared publicly by its author(s). These packages extend the core functionalities of Python. The Python Package Index (https://packt.live/37iTRXc) lists all the packages available in Python.

In this section, we will present to you two of the most popular ones: pandas and scikit-learn.

The pandas Package

The pandas package provides an incredible amount of APIs for manipulating data structures. The two main data structures defined in the pandas package are DataFrame and Series.

DataFrame and Series

A DataFrame is a tabular data structure that is represented as a two-dimensional table. It is composed of rows, columns, indexes, and cells. It is very similar to a sheet in Excel or a table in a database:

Figure 1.28: Components of a DataFrame

In Figure 1.28, there are three different columns: algorithm...