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 ...

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 ...

To get the most out of the book, basic knowledge of Python, including pandas and NumPy, as well as some experience working with datasets is required. This book is also ideal for anyone interested in ...

Ego network is a special type of network consisting of one central node and all other nodes directly connected to it. The central node is known as ego, while the other surrounding nodes directly ...

In this article I'll show you how to do time series regression using a neural network ... using Python. A good way to see where this article is headed is to take a look at the screenshot in Figure 1 ...

Our resident data scientist explains how to train neural networks with two popular variations of the back-propagation technique: batch and online. Training a neural network is the process of ...

One common approach is using a Retrieval-Augmented Generation (RAG ... environments where facts are constantly updated. Meet Graphiti: a Python library for building temporal Knowledge Graphs. Graphiti ...