"Machine Learning and Data Mining Annual Volume 2023" ed. by Marco Antonio Aceves-Fernández, Andries Engelbrecht

This book offers a multifaceted perspective on machine learning and data mining. Whether you’re an experienced researcher or a newcomer, this collection is an essential resource for staying at the forefront of these dynamic and influential disciplines.

The interest within the academic community regarding AI has experienced exponential growth in recent years. Several key factors have contributed to this surge in interest. Firstly, the rapid advancements in AI technologies have showcased their potential to revolutionize various fields, such as healthcare, finance, and transportation, sparking curiosity and enthusiasm among researchers and scholars. Secondly, the availability of vast amounts of data and computing power has enabled academics to delve deeper into AI research, exploring complex algorithms and models to tackle real-world problems. Additionally, the interdisciplinary nature of AI has encouraged collaboration among experts from diverse fields like computer science, neuroscience, psychology, and ethics, fostering a rich exchange of ideas and approaches.

Contents
1. Complexity Analysis in Channel Estimation Massive MIMO Compared with LMU and GRU
2. Artificial Intelligence Techniques for Political Risk Management: An NLP Analysis of the 2019 US-China Trade War
3. A Quantitative Analysis of Big Data Analytics Capabilities and Supply Chain Management
4. Application of Machine Learning in Geotechnical Engineering for Risk Assessment
5. Application of Machine Learning and Data Mining in Medicine: Opportunities and Considerations
6. Automatic BI-RADS Classification of Breast Magnetic Resonance Medical Records Using Transformer-Based Models for Brazilian Portuguese


More : You find here