Contact
Hoe winkelen bij ons werkt
Bezorging
Winkelgids
Probabilistic Machine Learning
Engels
353 b
TOP
Tot 30 dagen retourrecht
Klanten kochten ook
/
Paperback
59.37
€
/
Paperback
68.61
€
A detailed and up-to-date introduction to machine learning, presented through the unifying lens of probabilistic modeling and Bayesian decision theory.
This book offers a detailed and up-to-date introduction to machine learning (including deep learning) through the unifying lens of probabilistic modeling and Bayesian decision theory. The book covers mathematical background (including linear algebra and optimization), basic supervised learning (including linear and logistic regression and deep neural networks), as well as more advanced topics (including transfer learning and unsupervised learning). End-of-chapter exercises allow students to apply what they have learned, and an appendix covers notation.
Probabilistic Machine Learning grew out of the author’s 2012 book, Machine Learning: A Probabilistic Perspective. More than just a simple update, this is a completely new book that reflects the dramatic developments in the field since 2012, most notably deep learning. In addition, the new book is accompanied by online Python code, using libraries such as scikit-learn, JAX, PyTorch, and Tensorflow, which can be used to reproduce nearly all the figures; this code can be run inside a web browser using cloud-based notebooks, and provides a practical complement to the theoretical topics discussed in the book. This introductory text will be followed by a sequel that covers more advanced topics, taking the same probabilistic approach.
Informatie over het boek
Engels
Geef dit boek vandaag nog cadeau
Dat gaat heel eenvoudig
1 Voeg het boek toe aan je winkelwagentje en selecteer Als cadeau bezorgen 2 Je krijgt van ons per omgaand een voucher 3 Het boek wordt bezorgd op het adres van de ontvangerDit vind je misschien ook interessant
/
Paperback
61.08
€
Hoi! Ik ben Libroamiko, je boekadviseur.
Hoe kan ik je helpen?