What is this book about? Graph neural networks are a highly effective tool for analyzing data that can be represented as a graph, such as social networks, chemical compounds, or transportation ...

How to make line charts in Python with Plotly. Examples on creating and styling line charts in Python with Plotly. Plotly line charts are implemented as connected scatterplots (see below), meaning ...

Learn the best practices for using annotations to add context to a line chart, and how to apply them in your data mining projects. Annotations can help you communicate your insights and findings ...

In this section, we'll use the Seaborn library, which I've covered previously, to visualize statistical data with Python the way you would with a graphing calculator in a stats class.

Using Quarto with Observable JavaScript is a great solution for R and Python users who want to create more interactive and visually engaging reports.

Hands-On Graph Neural Networks Using Python begins with the fundamentals of graph theory and shows you how to create graph datasets from tabular data. As you advance, you’ll explore major graph neural ...