Probabilistic Machine Learning: An Introduction (Adaptive Computation and Machine Learning series) - Marjane Mall - Image 1
240
00DH
480.00 DH
-50%

Probabilistic Machine Learning: An Introduction (Adaptive Computation and Machine Learning series)

Livraison

Détails
Frais de livraison à partir de :
Livraison entre le Mercredi 9 septembre 2026 et le Jeudi 10 septembre 2026

À propos de cet article :

Marque : GENERIC
Vendu par KECHBOOK

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...

1

Mode de paiement

Paiement par carte bancaire
Carte marocaines
Paiement à la livraison
Paiement en espèce à la livraison
Politique de retours
Note de politique de retour

Description produit

Marque
GENERIC
Titre
Probabilistic Machine Learning: An Introduction (Adaptive Computation and Machine Learning series)
Éditeur
The MIT Press
Type de produit
paperback
Présentation du livre
paperback
Date de sortie
3/1/2022 12:00:00 AM
Langue d'origine
English
ISBN
262046822
Nombre de pages
864 pages
Langue
English
Résumé
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. Read more
Auteur
Kevin P. Murphy
Date de parution
3/1/2022 12:00:00 AM