A behind-the-scenes look at how a Cisco automation engineer replaced fragile CLI workflows with model-driven infrastructure that scales. NEW YORK, NY, UNITED STATES ...

Abstract: We propose an explainable topic modeling method that tracks user interests to elucidate their association with social events while ensuring high reliability and low computational cost.

Nonlinear relationships are common in applied research, especially in education, health, and economics. While Python provides statsmodels for mixed-effects models and patsy for spline construction, ...

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 ...

Explore advanced physics with **“Modeling Sliding Bead On Tilting Wire Using Python | Lagrangian Explained.”** In this tutorial, we demonstrate how to simulate the motion of a bead sliding on a ...

This study uses keyword filtering, a transformer-based algorithm, and inductive content coding to identify and characterize cannabis adverse experiences as discussed on the social media platform ...

GluonTS is a Python toolkit for probabilistic time series modeling, built around Apache MXNet (incubating). GluonTS provides utilities for loading and iterating over time series datasets, state of the ...

ABSTRACT: Accurate prediction of water travel time in drip irrigation systems is essential for efficient water and nutrient delivery. This study develops a predictive model for travel time by ...