BERTopic topic modeling worker for the Faculytics analysis pipeline. Deployed on RunPod serverless. Receives pre-cleaned text with pre-computed LaBSE embeddings, runs BERTopic clustering, and returns ...

Abstract: By modeling global word co-occurrence patterns, topic models aim to uncover the underlying semantic structure of a corpus. However, their effectiveness is often undermined in short texts due ...

Part 2 of modeling Faraday’s Law using Python. This tutorial explores electromagnetic induction through code and simulation to better understand changing magnetic fields and induced currents. #physics ...

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, ...

Outdated tracking can’t keep up with privacy changes. Unify first-party data, attribution, MMM, and incrementality to measure real impact. Overlapping attribution can inflate channel performance.

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 ...

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 ...

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 ...