Abstract: Scaling Machine Learning (ML) workflows in cloud environments presents critical challenges in ensuring reproducibility, low-latency inference, infrastructure reliability, and regulatory ...

Background: Depression affects more than 350 million people globally. Traditional diagnostic methods have limitations. Analyzing textual data from social media provides new insights into predicting ...

Washing machines aren’t what they used to be. Some new appliances have over a dozen cycles, and then there are a slew of other things to consider, including water temperature, spin speed, cycle ...

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.

1 School of Taxation and Public Administration, Shanghai Lixin University of Accounting and Finance, Shanghai, China. 2 School of Business, Computing and Social Sciences, University of Gloucestershire ...

If you’re learning machine learning with Python, chances are you’ll come across Scikit-learn. Often described as “Machine Learning in Python,” Scikit-learn is one of the most widely used open-source ...

Abstract: Using machine learning (ML)-based prediction models could significantly improve the precision and effectiveness of traditional air quality models. This article provides a comprehensive ...

Objective: This study aims to develop and validate a machine learning model that integrates dietary antioxidants to predict cardiovascular disease (CVD) risk in diabetic patients. By analyzing the ...

So alleges Retraction Watch (Rita Aksenfeld): Based on a tip from a reader, we checked 18 of the 46 citations in the book {Mastering Machine Learning: From Basics to Advanced}. Two-thirds of them ...

The design and application of engineered biochar is crucial for removing contaminants from soil and water,yet its development and commercialization still depend on time- and labor-intensive ...