Geometry of Deep Learning: A Signal Processing Perspective / Najlacnejšie knihy
Geometry of Deep Learning: A Signal Processing Perspective

Kód: 42594441

Geometry of Deep Learning: A Signal Processing Perspective

The focus of this book is on providing students with insights into geometry that can help them understand deep learning from a unified perspective. Rather than describing deep learning as an implementation technique, as is usually ... celý popis

76.13


Skladom u dodávateľa v malom množstve
Odosielame za 12 - 15 dní

Potrebujete viac kusov?Ak máte záujem o viac kusov, preverte, prosím, najprv dostupnosť titulu na našej zákazníckej podpore.


Pridať medzi želanie

Mohlo by sa vám tiež páčiť

Darujte túto knihu ešte dnes
  1. Objednajte knihu a vyberte Zaslať ako darček.
  2. Obratom obdržíte darovací poukaz na knihu, ktorý môžete ihneď odovzdať obdarovanému.
  3. Knihu zašleme na adresu obdarovaného, o nič sa nestaráte.

Viac informácií

Viac informácií o knihe Geometry of Deep Learning: A Signal Processing Perspective

Nákupom získate 191 bodov

Anotácia knihy

The focus of this book is on providing students with insights into geometry that can help them understand deep learning from a unified perspective. Rather than describing deep learning as an implementation technique, as is usually the case in many existing deep learning books, here, deep learning is explained as an ultimate form of signal processing techniques that can be imagined. To support this claim, an overview of classical kernel machine learning approaches is presented, and their advantages and limitations are explained. Following a detailed explanation of the basic building blocks of deep neural networks from a biological and algorithmic point of view, the latest tools such as attention, normalization, Transformer, BERT, GPT-3, and others are described. Here, too, the focus is on the fact that in these heuristic approaches, there is an important, beautiful geometric structure behind the intuition that enables a systematic understanding. A unified geometric analysis to understand the working mechanism of deep learning from high-dimensional geometry is offered. Then, different forms of generative models like GAN, VAE, normalizing flows, optimal transport, and so on are described from a unified geometric perspective, showing that they actually come from statistical distance-minimization problems.Because this book contains up-to-date information from both a practical and theoretical point of view, it can be used as an advanced deep learning textbook in universities or as a reference source for researchers interested in acquiring the latest deep learning algorithms and their underlying principles. In addition, the book has been prepared for a codeshare course for both engineering and mathematics students, thus much of the content is interdisciplinary and will appeal to students from both disciplines.

Parametre knihy

Zaradenie knihy Knihy po nemecky Naturwissenschaften, Medizin, Informatik, Technik Informatik, EDV Informatik

76.13

Obľúbené z iného súdka



Osobný odber Bratislava a 2642 dalších

Copyright ©2008-24 najlacnejsie-knihy.sk Všetky práva vyhradenéSúkromieCookies


Môj účet: Prihlásiť sa
Všetky knihy sveta na jednom mieste. Navyše za skvelé ceny.

Nákupný košík ( prázdny )

Vyzdvihnutie v Zásielkovni
zadarmo nad 59,99 €.

Nachádzate sa: