… At first, we introduce the key concepts related to machine learning. Then, we present …
machine learning in e-learning context. Keywords—E-learning, Technology Enhanced Learning …

… of trustworthiness technologies for machine learning, namely these … technologies in all
stages of the life cycle. In so doing we establish the ways in which machine learning technologies …

… Explaining the results of machine learning models. Artificial … the machine learning technologies.
Despite this, there are potential risks associated with a “black box” approach to learning. …

… In this paper, we analyze machine learning techniques and intro… of machine learning based
6G systems. To realize the network intelligentization in future 6G systems, machine learning …

… machine learning (ML) forms a typical representative algorithm category used to achieve
predictions and judgments by analyzing and learning … SG and EI technologies, takes the typical …

… Several promising machine learning techniques can be used for … learning, deep learning,
distributed and parallel learning, transfer learning, active learning, and kernel-based learning. …

… In this project, big data technologies and machine learning techniques based on deep
learning and artificial intelligence are used to exploit the millions of data offered by the intelligent …

… research dedicated to applications of machine learning in agricultural production systems. …
will benefit from machine learning technologies. By applying machine learning to sensor data, …

… Machine learning mechanisms are characterized by the time … theoretical foundations for
machine learning and the leading … on machine learning and Deep Reinforcement Learning (DRL…

… Data-driven machine learning (ML) techniques have demonstrated superior predictive
capability compared to conventional methods for modeling such highly complex processes. …