Isbn: 9780850145137 - machine learning and data mining annual volume 2023 (artificial intelligence, band 21) (4 Ergebnisse)

Hardcover. Zustand: Brand New. 150 pages. 7.00x0.55x10.00 inches. In Stock.

Buch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 150 pp. Englisch.

Buch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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. With contributions from a diverse group of authors, this book offers a multifaceted perspective on machine learning and data mining. Whether yoüre an experienced researcher or a newcomer, this collection is an essential resource for staying at the forefront of these dynamic and influential disciplines.Books on Demand GmbH, Überseering 33, 22297 Hamburg 150 pp. Englisch.…

Buch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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. With contributions from a diverse group of authors, this book offers a multifaceted perspective on machine learning and data mining. Whether yoüre an experienced researcher or a newcomer, this collection is an essential resource for staying at the forefront of these dynamic and influential disciplines.…