Passive sensing via wearable devices and smartphones, combined with machine learning (ML), enables objective, continuous, and noninvasive mental health monitoring. Objective: This study aimed to ...

The 3rd Workshop on Causal Inference and Machine Learning in Practice at KDD 2025 aims to bring together researchers, industry professionals, and practitioners to explore the application of causal ...

Abstract: In this paper, a hybrid PCA-based approach is proposed for predicting the respiratory imbalance in an urban health monitoring system. To do this, three models namely Random Forest, XGBoost, ...

Choose your path! This repository prepares you for multiple ML/AI careers. Select your target role to see a customized learning path: Role Focus Est. Time Key Modules ...

The emerging field of digital phenotyping leverages the numerous sensors embedded in a smartphone to better understand its user's current psychological state and behavior, enabling improved health ...

Abstract: Principal Components Analysis (PCA) is a popular dimensionality reduction and feature selection technique. It works by swiping non-informative features while retaining those that are still ...

Simplify complex datasets using Principal Component Analysis (PCA) in Python. Great for dimensionality reduction and visualization. Gingrich: Time for 'national conversation' about immigrants living ...