Abstract: Adversarial machine learning (AML) attacks have become a major concern for organizations in recent years, as AI has become the industry’s focal point and GenAI applications have grown in ...

From fine-tuning open source models to building agentic frameworks on top of them, the open source world is ripe with ...

Explore a programming languages list with top coding languages explained, their uses, job prospects, and how to choose the ...

MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data other than what they were trained on, raising questions about the need to ...

This workshop will consider several applications based on machine learning classification and the training of artificial neural networks and deep learning.

With countless applications and a combination of approachability and power, Python is one of the most popular programming ...

To help professionals build these capabilities, we have curated a list of the best applied AI and data science courses.

Overview: Master deep learning with these 10 essential books blending math, code, and real-world AI applications for lasting ...

An interatomic potential is a set of mathematical rules that describes the complex dance of forces between atoms — how atomic ...

Abstract: The rapid growth of machine learning (ML) technologies has raised significant concerns about their environmental impact, particularly regarding energy consumption and carbon emissions. This ...

Learn how to build a perceptron from scratch in Python! This tutorial covers the theory, coding, and practical examples, helping you understand the foundations of neural networks and machine learning.

Treescope is an interactive HTML pretty-printer and N-dimensional array ("tensor") visualizer, designed for machine learning and neural networks research in IPython notebooks. It's a drop-in ...