Machine Learning and Data Mining: Theory and Applications
Topic Information
Dear Colleagues,
Recent decades have witnessed a rapid evolution of machine learning (ML) and data mining (DM) techniques, driven by advances in computing power, big data, and artificial intelligence. These technologies have transformed diverse domains such as healthcare, finance, manufacturing, transportation, and smart environments. This Topic aims to gather high-quality contributions that explore both the theoretical foundations and practical applications of ML and DM. We welcome research on emerging algorithms, optimization strategies, and innovative architectures, as well as studies addressing real-world challenges through predictive modeling, pattern recognition, and knowledge discovery. Particular attention will be given to works that integrate ML and DM with cutting-edge paradigms such as deep learning, IoT, cloud computing, and ethical AI.
Prof. Dr. Jonathan Cepeda-Negrete
Prof. Dr. Qianmu Li
Topic Editors
Keywords
- machine learning
- data mining
- artificial intelligence
- deep learning
- big data analytics
- pattern recognition
- predictive modeling
- computer vision
- IoT and smart systems