Machine learning sounds math-heavy, but modern tools make it far more accessible. Here’s how I built models without deep math ...

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 ...

Objective: This study evaluated the feasibility of using a smartphone app to predict mental health risks in non-clinical adolescents by integrating active and passive data streams within a machine ...

Proper waste sorting is very important for keeping our neighbourhoods clean and saving resources for the future. When we mix ...

Abstract: Jupyter notebooks have become central in data science, integrating code, text and output in a flexible environment. With the rise of machine learning (ML), notebooks are increasingly used ...

Python has become the go-to language for data analysis, automation, and machine learning thanks to its simplicity, versatility, and powerful libraries. From NumPy’s lightning-fast arrays to ...

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...

Copyright: © 2025 The Author(s). Published by Elsevier Ltd. Machine learning for health data science, fuelled by proliferation of data and reduced computational ...

Machine learning models are increasingly applied across scientific disciplines, yet their effectiveness often hinges on heuristic decisions such as data transformations, training strategies, and model ...