Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...

Dive into Faraday’s Law of Electromagnetic Induction with a practical Python implementation in this first part of our Electrodynamics series. Learn how to simulate and visualize changing magnetic ...

Take your physics and coding skills to the next level with **“Learn To Calculate Launch Angles In Projectile Motion Using Python.”** This tutorial combines the fundamentals of projectile motion with ...

verl is a flexible, efficient and production-ready RL training library for large language models (LLMs). verl is the open-source version of HybridFlow: A Flexible and Efficient RLHF Framework paper.

Recently, there have been significant research interests in training large language models (LLMs) with reinforcement learning (RL) on real-world tasks, such as multi-turn code generation. While online ...

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 ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...

Abstract: Selecting targets to attack and assigning weapons are among the most critical decisions on the battlefield. The decision problem is represented as a dynamic weapon-target assignment (DWTA) ...

AI can be used to produce clinically meaningful radiology reports using medical images like chest x-rays. Medical image report generation can reduce reporting burden while improving workflow ...

Abstract: Asthma exacerbation prediction is critical for preventing severe respiratory complications and improving patient outcomes. Traditional predictive models rely on static machine learning ...