Abstract: Author-topic modeling explores relationships among authors, documents, topics, and words. While traditional Bayesian methods extended Latent Dirichlet Allocation (LDA), recent neural ...

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 ...

Free-text responses came from 34% (1220/3579) of motivated and 64% (153/240) of neutral participants. Biterm topic modeling revealed motivated participants emphasized early detection benefits, health ...

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 ...

Abstract: Topic modeling automatically discovers the main underlying themes in a collection of texts by grouping related words into topics. It is widely used for organizing, searching, and summarizing ...

Bayesian marketing toolbox in PyMC. Media Mix (MMM), customer lifetime value (CLV), buy-till-you-die (BTYD) models and more.

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 ...