Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track

Discover the groundbreaking insights in "Machine Learning and Knowledge Discovery in Databases: Applied Data Science Track," authored by Yuxiao Dong. This essential volume, published by Springer Nature Switzerland AG in 2021, spans an impressive 516 pages, making it a comprehensive resource for both practitioners and researchers in the field of data science.

This first edition compiles the refereed proceedings from the European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD 2021), held from September 13-17, 2021. Dive into the latest advancements and methodologies in machine learning, as well as innovative techniques for knowledge discovery in databases.

Whether you are a seasoned expert or a newcomer to data science, this book is an invaluable addition to your library, offering practical applications and theoretical insights that will enhance your understanding of the rapidly evolving landscape of machine learning.