Book Image

The Applied Data Science Workshop - Second Edition

By : Alex Galea
Book Image

The Applied Data Science Workshop - Second Edition

By: Alex Galea

Overview of this book

From banking and manufacturing through to education and entertainment, using data science for business has revolutionized almost every sector in the modern world. It has an important role to play in everything from app development to network security. Taking an interactive approach to learning the fundamentals, this book is ideal for beginners. You’ll learn all the best practices and techniques for applying data science in the context of real-world scenarios and examples. Starting with an introduction to data science and machine learning, you’ll start by getting to grips with Jupyter functionality and features. You’ll use Python libraries like sci-kit learn, pandas, Matplotlib, and Seaborn to perform data analysis and data preprocessing on real-world datasets from within your own Jupyter environment. Progressing through the chapters, you’ll train classification models using sci-kit learn, and assess model performance using advanced validation techniques. Towards the end, you’ll use Jupyter Notebooks to document your research, build stakeholder reports, and even analyze web performance data. By the end of The Applied Data Science Workshop, you’ll be prepared to progress from being a beginner to taking your skills to the next level by confidently applying data science techniques and tools to real-world projects.
Table of Contents (8 chapters)

Introduction

So far in this book, we have focused on using Jupyter to build reproducible data analysis and modeling workflows. We'll continue with a similar approach in this chapter, but with the main focus being on data acquisition. In particular, we will show you how data can be acquired from the web using HTTP requests. This will involve making API requests and scraping web pages by parsing HTML. In addition to these new topics, we'll continue to use pandas for building and transforming our datasets.

Before we cover HTTP requests and how to use them in Python, we'll discuss the importance of gathering data from the web in general. The amount of data that's available online is huge, and it's continuously growing at a staggering pace. Additionally, it's becoming increasingly important for driving business growth. Consider, for example, the ongoing global shift from technologies such as newspapers, magazines, and TV to online content. With customized...