The past few years have seen an explosion in the use of graph neural networks, with their application ranging from natural language processing and computer vision to recommendation systems and drug ...

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 ...

Get started with the Microsoft Graph SDK for Python by integrating the Microsoft Graph API into your Python application. Note: This SDK allows you to build applications using the v1.0 of Microsoft ...

Make inference on the fully trained TransE model using the following command. pykg2vec-infer -mn TransE Wrapping up. Pykg2vec is a versatile Python library for training, testing, experimenting, ...

Call graphs play an important role in different contexts, such as profiling and vulnerability propagation analysis. Generating call graphs in an efficient manner can be a challenging task when it ...

Using Quarto with Observable JavaScript is a great solution for R and Python users who want to create more interactive and visually engaging reports. There’s an intriguing new option for people ...

Find out what makes Python a versatile powerhouse for modern software development—from data science to machine learning, systems automation, web and API development, and more.