Machine learning models, particularly commercial ones, generally do not list the data developers used to train them. Yet what models contain and whether that material can be elicited with a particular ...

Learn how to implement SGD with momentum from scratch in Python—boost your optimization skills for deep learning. Cuba is already on the brink. Maduro’s ouster brings it closer to collapse. California ...

Self-driving vehicles rely closely on interactions with humans, vehicles, and the surrounding environment. However, the interactive analysis of self-driving is impacted by multiple perception sources, ...

ABSTRACT: Despite its significant impacts on climate, environment, and public health, air pollution monitoring in Africa is still sparse. This study developed a machine learning framework of four ...

This workshop will provide an introduction to the types of theories, models, and frameworks (TMFs) commonly used in dissemination and implementation science, including pros and cons and application of ...

This library contains a pure-Python implementation of the HMAC-based key derivation function (HKDF) as specified in RFC 5869. The order and names of arguments within the function signatures in this ...

aDivision of Pediatric Critical Care Medicine, Department of Anesthesiology and Critical Care Medicine, Children's Hospital of Philadelphia, Perelman School of Medicine, University of Pennsylvania, ...

This repository contains a Python-based project for real-time healthcare monitoring, focusing on forecasting patient heart rates using the ARIMA (AutoRegressive Integrated Moving Average) model. The ...

Written by Ken Huang, CSA Fellow, Co-Chair of CSA AI Safety Working Groups and Dr. Ying-Jung Chen, Georgia Institute of Technology. This implementation guide provides a comprehensive, hands-on ...

In this tutorial, we demonstrate how to use the UAgents framework to build a lightweight, event-driven AI agent architecture on top of Google’s Gemini API. We’ll start by applying nest_asyncio to ...