Book Image

Python Machine Learning Blueprints - Second Edition

By : Alexander Combs, Michael Roman
Book Image

Python Machine Learning Blueprints - Second Edition

By: Alexander Combs, Michael Roman

Overview of this book

Machine learning is transforming the way we understand and interact with the world around us. This book is the perfect guide for you to put your knowledge and skills into practice and use the Python ecosystem to cover key domains in machine learning. This second edition covers a range of libraries from the Python ecosystem, including TensorFlow and Keras, to help you implement real-world machine learning projects. The book begins by giving you an overview of machine learning with Python. With the help of complex datasets and optimized techniques, you’ll go on to understand how to apply advanced concepts and popular machine learning algorithms to real-world projects. Next, you’ll cover projects from domains such as predictive analytics to analyze the stock market and recommendation systems for GitHub repositories. In addition to this, you’ll also work on projects from the NLP domain to create a custom news feed using frameworks such as scikit-learn, TensorFlow, and Keras. Following this, you’ll learn how to build an advanced chatbot, and scale things up using PySpark. In the concluding chapters, you can look forward to exciting insights into deep learning and you'll even create an application using computer vision and neural networks. By the end of this book, you’ll be able to analyze data seamlessly and make a powerful impact through your projects.
Table of Contents (13 chapters)

Parsing the DOM to extract pricing data

The DOM is the collection of elements that comprise a web page. It includes HTML tags such as body and div, as well as the classes and IDs embedded within these tags.

Let's take a look at the DOM for our Google page:

  1. To see it, right-click on the page and click on Inspect. This should be the same for Firefox or Chrome. This will open the developer tab that allows you to see the page source information, as demonstrated in the following screenshot:
  1. Once this is open, choose the element selector in the upper left-hand corner, and click on an element to jump to that element in the page source code:

  1. The element that we are concerned with is the box that contains the flight information. This can be seen in the following screenshot:

If you look closely at the element, you will notice that it is an element called a div. This div...