UID:
almahu_9949434904802882
Umfang:
1 online resource
Ausgabe:
First edition.
ISBN:
9781003002611
,
1003002617
,
9781000818253
,
100081825X
,
9781000818222
,
1000818225
Inhalt:
"Machine Learning: Theory and Practice provides an introduction to the most popular methods in machine learning. The book covers regression including regularization, tree-based methods including Random Forests and Boosted Trees, Artificial Neural Networks including Convolutional Neural Networks (CNNs), reinforcement learning, and unsupervised learning focused on clustering. Topics are introduced in a conceptual manner along with necessary mathematical details. The explanations are lucid, illustrated with figures and examples. For each machine learning method discussed, the book presents appropriate libraries in the R programming language along with programming examples"--
Weitere Ausg.:
Print version: Kalita, Jugal Kumar. Machine learning Boca Raton : Chapman & Hall/CRC Press, 2023 ISBN 9780367433543
Sprache:
Englisch
DOI:
10.1201/9781003002611
URL:
https://www.taylorfrancis.com/books/9781003002611
Bookmarklink
