Learn how to use permutation testing to validate your machine learning models using Sklearn. This video breaks down the process to help improve model reliability and performance.

Programming efficient asynchronous systems is challenging because it can often be hard to express the design declaratively, or to defend against interleaving-dependent bugs such as data races and ...

The XGBoost model predicts hyperglycemia risk in psoriasis patients with high accuracy, achieving an AUC of 0.821 in the training set. A web-based calculator was developed to facilitate personalized ...

Abstract: After all advancements in technology and times, prediction and prevention of heart diseases is still a major issue in modern days. Heart diseases play a major role in high death rate in ...

The tensile testing machine described here is a fully open-source device designed to determine the mechanical tensile strength of test specimens. At its core, it uses a single-board computer ...

Abstract: Modern image recognition has experienced dramatic improvements because of Machine Learning and Deep Learning algorithms together. This study investigates CNNs and SVMs for recognition ...

We introduce PaCoRe (Parallel Coordinated Reasoning), a framework that shifts the driver of inference from sequential depth to coordinated parallel breadth, breaking the model context limitation and ...

Background: Cognitive impairment in Parkinson’s disease (PD-CI) is a prevalent non-motor symptom, significantly diminishing quality of life and imposing a substantial family burden. Effective ...

Spotify Technology SA will begin testing a new feature that allows users to type an idea for a playlist into the app and receive a unique set of songs based on their historical taste and behavior. The ...