(final Release)

Graph Neural Networks in Action teaches you to build cutting-edge graph neural networks for recommendation engines, molecular modeling, and more. This comprehensive guide contains coverage of the essential GNN libraries, including PyTorch Geometric, DeepGraph Library, and Alibaba’s GraphScope for training at scale.

Why is Google Analytics 4 the most modern data model available for digital marketing analytics? Because rather than simply report what has happened, GA4's new cloud integrations enable more data activation–linking online and offline data across all your streams to provide end-to-end marketing data. This practical book prepares you for the future of digital marketing by demonstrating how GA4 supports these additional cloud integrations.

Keep sensitive user data safe and secure without sacrificing the performance and accuracy of your machine learning models.

This practical guide provides more than 200 self-contained recipes to help you solve machine learning challenges you may encounter in your work. If you're comfortable with Python and its libraries, including pandas and scikit-learn, you'll be able to address specific problems all the way from loading data to training models and leveraging neural networks.

Citizen data analysts are emerging to fill in the gaps left by traditional and slow business intelligence processes. Business functions such as finance, supply chain, and sales are now leading new data/analytics initiatives rather than partnering with centralized IT or analytics teams. But there is a knowledge gap—these new "citizen data analysts" understand their area of business, but unlike their IT counterparts, they do not have a background in data processing technology.