In my latest Signal Spot, I had my Villanova students explore machine learning techniques to see if we could accurately ...

digna has released version 2026.04 of its data quality and observability platform, introducing enhanced time-series analytics ...

Abstract: Many existed example-based super-resolution algorithms focus on learning a regression function which maps a low-resolution image patch to a high-resolution image patch. Even though this ...

Implement Logistic Regression in Python from Scratch ! In this video, we will implement Logistic Regression in Python from Scratch. We will not use any build in models, but we will understand the code ...

In many AI applications today, performance is a big deal. You may have noticed that while working with Large Language Models (LLMs), a lot of time is spent waiting—waiting for an API response, waiting ...

In forecasting economic time series, statistical models often need to be complemented with a process to impose various constraints in a smooth manner. Systematically imposing constraints and retaining ...

JSON Prompting is a technique for structuring instructions to AI models using the JavaScript Object Notation (JSON) format, making prompts clear, explicit, and machine-readable. Unlike traditional ...

🔍 Motivation: Can we develop deep learning models that efficiently operate on voxel-level fMRI data - just like we do with other medical imaging modalities? 🧠 Architecture: We introduce BrainMT, a ...