characterized by a reduced energy footprint, utilizing machine learning (ML) algorithms to predict consumer preferences within the …

machine learning techniques are employed to flag potential anomalies, the challenge lies in evaluating the significance of …

Interest in predicting sports match outcomes has grown significantly, driven by advancements in machine learning … remains relatively limited. We propose a methodology that combines machine learning and algorithm explainability techniques …

effectiveness in production management. Consequently, machine learning models have become essential for decision-making in this …

understanding cyber threats through geographical insights. The primary objective is to develop unsupervised machine learning models …

use of generative AI tools like ChatGPT (30%), followed by other advanced technologies, such as GPT-4, machine learning …

advanced machine learning and deep learning models is still missing. This study aims to fill that gap by systematically …

. This study developed a machine learning framework to automate doctor response patterns for mental health questions … methods: Word2Vec, Bag-of-Words, N-Gram, and Global Vectors for Word Representation. Five machine learning algorithms - Naïve … results. This work demonstrates that machine learning can automate mental health responses at scale, with Gradient Boosting …

data. In contrast, artificial intelligence technologies, including machine learning, anomaly detection, and natural …