Use the vitals package with ellmer to evaluate and compare the accuracy of LLMs, including writing evals to test local models.

Learn how to model 1D motion in Python using loops! 🐍⚙️ This step-by-step tutorial shows you how to simulate position, velocity, and acceleration over time with easy-to-follow Python code. Perfect ...

Learn how to model a mass-spring system using Python in this step-by-step tutorial! 🐍📊 Explore how to simulate oscillations, visualize motion, and analyze energy in a spring-mass system with code ...

Humanities students can now enter data science and AI without an engineering degree. Here’s a clear roadmap to start your tech journey ...

💻 local machines, e.g., macOS (+ Apple Silicon/MPS) and Linux/Windows WSL (+ NVIDIA GPU). 🌐 Remote Linux servers with GPUs, e.g., VMs on cloud providers and IC and RCP HaaS at EPFL. ☁️ Managed ...

Finding the right book can make a big difference, especially when you’re just starting out or trying to get better. We’ve ...

The CBSE Class 12 Informatics Practices exam will be held on March 25. As 50% of the 2026 paper is expected to be competency-based, students should focus on high-weightage topics like DataFrames, SQL ...

Abstract: Though significant progress has been achieved on fine-grained visual classification (FGVC), severe overfitting still hinders model generalization. A recent study shows that hard samples in ...

Aaron has a burning passion for flying and traveling around the world. He has flown around the world numerous times while making a point of visiting aviation museums around the world. He hails from ...

From the Department of Bizarre Anomalies: Microsoft has suppressed an unexplained anomaly on its network that was routing traffic destined to example.com—a domain reserved for testing purposes—to a ...

An exercise-driven course on Advanced Python Programming that was battle-tested several hundred times on the corporate-training circuit for more than a decade. Written by David Beazley, author of the ...

Abstract: Recent studies have revealed that Deep Neural Networks (DNNs) are highly vulnerable to adversarial examples, which are generated by introducing imperceptible perturbations to clean images, ...