Machine Learning and Knowledge Extraction is an international academic journal dedicated to the fields of machine learning, data mining, knowledge discovery, and artificial intelligence. This journal is committed to publishing original research papers, review articles, and case studies, with the aim of promoting theoretical development and practical applications in these fields.

This journal covers multiple aspects of machine learning, including but not limited to deep learning, clustering analysis, classification algorithms, regression analysis, reinforcement learning, and neural networks. At the same time, the journal also focuses on the application of knowledge extraction and data mining techniques in fields such as bioinformatics, medicine, social sciences, and business intelligence, emphasizing the extraction of useful information and patterns from big data to support decision-making and innovative research. The editorial team and review experts of the magazine come from around the world, and they are all leading figures in their respective fields, ensuring the high quality and innovation of the journal content. Through rigorous peer review, the journal ensures the academic value and scientific accuracy of published articles, providing a platform for researchers, engineers, scholars, and industry experts worldwide to share the latest research findings and cutting-edge technologies.