The success of machine learning (ML) techniques in the formerly difficult areas of data
analysis and pattern extraction has led to their widespread incorporation into various …

Machine learning (ML) has succeeded in improving our daily routines by enabling
automation and improved decision making in a variety of industries such as healthcare …

Agriculture is essential to a flourishing economy. Although soil is essential for sustainable
food production, its quality can decline as cultivation becomes more intensive and demand …

This research paper explores the challenges, solutions, and impact of implementing
machine learning (ML) models in business analytics. It delves into the complexities of …

The purpose of this study is to investigate and compare the popularity of common grocery
apps in Hungary as well as Iran. The data were gathered from Iranian and Hungarian users …

The utilization of Machine Learning (ML) has become widespread across several
disciplines. ML is utilized as an effective support mechanism in clinical diagnostics due to …

The agricultural sector plays a pivotal role in driving the economy of many developing
countries. Any dent in this economical structure may have a severe impact on a country's …

Proper calibration of human reliance on AI is fundamental to achieving complementary
performance in AI-assisted human decision-making. Most previous works focused on …

Food waste reduction, as a major application area of the Internet of Things (IoT) and big data
technologies, has become one of the most pressing issues. In recent years, there has been …

Machine Learning (ML) and Deep Learning (DL) are derivatives of Artificial Intelligence (AI)
that have already demonstrated their effectiveness in a variety of domains, including …