The next generation of financial crime prevention will be built on smarter architectures, not bigger data pools.

Abstract: Reinforcement Learning (RL) serves as a fundamental learning paradigm in the field of artificial intelligence, enabling decision-making policies through interactions with environments.

In this tutorial, we build a safety-critical reinforcement learning pipeline that learns entirely from fixed, offline data rather than live exploration. We design a custom environment, generate a ...

The field of medicine and medical imaging (X-rays, MRIs, CT scans, etc.) is rich in data, creating fertile ground for Artificial Intelligence (AI). Machine learning models, particularly deep neural ...

This is the Flower tutorial repository for PyCon DE & PyData 2025 talk "The Future of AI is Federated". It describes the prerequisites to setup your tutorial environment and outlines the 3 parts of ...

Sandia National Laboratories released information today spotlighting what the labs call a significant milestone in advancing artificial intelligence for national security. Over the past year, Sandia, ...

Editor's note: The IAPP is policy neutral. We publish contributed opinion and analysis pieces to enable our members to hear a broad spectrum of views in our domains. Artificial intelligence depends on ...

Learn about DenseNet, one of the most powerful deep learning architectures, in this beginner-friendly tutorial. Understand its structure, advantages, and how it’s used in real-world AI applications.

In this tutorial, we explore the power of self-supervised learning using the Lightly AI framework. We begin by building a SimCLR model to learn meaningful image representations without labels, then ...

Ritwik is a passionate gamer who has a soft spot for JRPGs. He's been writing about all things gaming for six years and counting. No matter how great a title's gameplay may be, there's always the ...