Explore how and why machine learning algorithms work with this self-contained, hands-on introduction using Matlab and Python.
Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
Ruye Wang is an Emeritus Professor of Engineering at Harvey Mudd College, with over thirty years of experience in teaching courses in Engineering and Computer Science. Previously a Principal Investigator at the Jet Propulsion Laboratory, NASA, his research interests include image processing, computer vision, machine learning and remote sensing. He is the author of the textbook Introduction to Orthogonal Transforms (2012).
„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.
Anbieter: Books From California, Simi Valley, CA, USA
hardcover. Zustand: Very Good. Artikel-Nr. mon0004071432
Anzahl: 3 verfügbar
Anbieter: Books From California, Simi Valley, CA, USA
hardcover. Zustand: Fine. Artikel-Nr. mon0004059401
Anzahl: 19 verfügbar
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
Zustand: New. In. Artikel-Nr. ria9781316519509_new
Anzahl: Mehr als 20 verfügbar
Anbieter: Majestic Books, Hounslow, Vereinigtes Königreich
Zustand: New. Artikel-Nr. 409287320
Anzahl: 4 verfügbar
Anbieter: Kennys Bookstore, Olney, MD, USA
Zustand: New. 2025. hardcover. . . . . . Books ship from the US and Ireland. Artikel-Nr. V9781316519509
Anzahl: Mehr als 20 verfügbar
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
Hardcover. Zustand: Brand New. 668 pages. 7.00x1.25x10.00 inches. In Stock. Artikel-Nr. xr1316519503
Anzahl: 2 verfügbar
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Emphasizing how and why machine learning algorithms work, this introductory textbook bridges the gap between the theoretical foundations of machine learning and its practical algorithmic and code-level implementation. Over 85 thorough worked examples, in both Matlab and Python, demonstrate how algorithms are implemented and applied whilst illustrating the end result. Over 75 end-of-chapter problems empower students to develop their own code to implement these algorithms, equipping them with hands-on experience. Matlab coding examples demonstrate how a mathematical idea is converted from equations to code, and provide a jumping off point for students, supported by in-depth coverage of essential mathematics including multivariable calculus, linear algebra, probability and statistics, numerical methods, and optimization. Accompanied online by instructor lecture slides, downloadable Python code and additional appendices, this is an excellent introduction to machine learning for senior undergraduate and graduate students in Engineering and Computer Science. Artikel-Nr. 9781316519509
Anzahl: 1 verfügbar