A Hands-On Introduction to Machine Learning - Couverture rigide

Shah, Chirag

 
9781009123303: A Hands-On Introduction to Machine Learning
Couverture rigide
ISBN 10 : 1009123300 ISBN 13 : 9781009123303
Editeur : Cambridge University Press, 2022

Synopsis

Packed with real-world examples, industry insights and practical activities, this textbook is designed to teach machine learning in a way that is easy to understand and apply. It assumes only a basic knowledge of technology, making it an ideal resource for students and professionals, including those who are new to computer science. All the necessary topics are covered, including supervised and unsupervised learning, neural networks, reinforcement learning, cloud-based services, and the ethical issues still posing problems within the industry. While Python is used as the primary language, many exercises will also have the solutions provided in R for greater versatility. A suite of online resources is available to support teaching across a range of different courses, including example syllabi, a solutions manual, and lecture slides. Datasets and code are also available online for students, giving them everything they need to practice the examples and problems in the book.

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À propos de l'auteur

Dr. Chirag Shah is a Professor of Information Science at the University of Washington (UW) in Seattle, USA. Before UW, he was at Rutgers University. His research focuses on intelligent information access systems that are also fair, transparent, and trustworthy. Dr. Shah teaches in undergraduate, masters, and Ph.D. programs at UW, focusing on data science and machine learning. He has designed MOOCs and taught several tutorials and short courses at international venues. Dr. Shah has written several books, including the bestselling textbook A Hands-On Introduction to Data Science (2020). He has visited and worked with many tech companies, including Amazon, Brainly, Getty Images, Microsoft Research, and Spotify.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
Cambridge University Press
Date d'édition
2022
Langue
anglais
ISBN 10 
1009123300
ISBN 13 
9781009123303
Reliure
Relié
Nombre de pages
500
Coordonnées du fabricant
non disponible
Personne responsable
Avery
https://www.avery.fr/

chemin des peupliers 27
Dardilly
France