Machine Learning with Quantum Computers - Francesco Petruccione,Maria Schuld
-30% ar kodu BOOKS
Piegāde 17-23 darba dienu laikā
30 dienu atgriešanas politika
This book offers an introduction into quantum machine learning research, covering approaches that range from "near-term" to fault-tolerant quantum machine learning algorithms, and from theoretical to practical techniques that help us understand how quantum computers can learn from data. Among the topics discussed are parameterized quantum circuits, hybrid optimization, data encoding, quantum feature maps an ... Pilns apraksts
Jums varētu patikt arī
TOP
Gödel, Escher, Bach: An Eternal Golden Braid
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
If Anyone Builds It, Everyone Dies: Why Superhuman AI Would Kill Us All
Eliezer Yudkowsky, Nate Soares
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
AI Engineering: Building Applications with Foundation Models
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Empire of AI: Dreams and Nightmares in Sam Altman's OpenAI
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
The Pragmatic Programmer: journey to mastery, 20th Anniversary Edition, 2/e: your journey to mastery, 20th Anniversary Edition
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
How To Think About AI: A Guide For The Perplexed
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Slanted 47 Digital Tools: Slanted Magazine
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
The Web Application Hacker's Handbook: Discovering and Exploiting Security Flaws
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
The Art of Game Design: A Book of Lenses
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
How Linux Works: What Every Superuser Should Know
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Artificial Intelligence: A Modern Approach, Global Edition
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Python Crash Course: A Hands-On, Project-Based Introduction to Programming
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
CompTIA Security+ Certification Kit: Exam SY0-701
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Automate the Boring Stuff with Python
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Fundamentals of Software Architecture: A Modern Engineering Approach
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Speak Data: Artists, Scientists, Thinkers, and Dreamers on How We Live Our Lives in Numbers
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Linux Basics for Hackers, 2nd Edition: Getting Started with Networking, Scripting, and Security in Kali
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
HBR Guide to Generative AI for Managers
-30% ar kodu BOOKS
Piegādātāja noliktavā
TOP
Hackers. 25th Anniversary Edition: Heroes of the Computer Revolution
-30% ar kodu BOOKS
Piegādātāja noliktavā
Aprašymas
This book offers an introduction into quantum machine learning research, covering approaches that range from "near-term" to fault-tolerant quantum machine learning algorithms, and from theoretical to practical techniques that help us understand how quantum computers can learn from data. Among the topics discussed are parameterized quantum circuits, hybrid optimization, data encoding, quantum feature maps and kernel methods, quantum learning theory, as well as quantum neural networks. The book aims at an audience of computer scientists and physicists at the graduate level onwards. The second edition extends the material beyond supervised learning and puts a special focus on the developments in near-term quantum machine learning seen over the past few years.
Vairāk informācijas
| Autors | Francesco Petruccione, Maria Schuld |
|---|---|
| Izdevējs | Springer Nature Switzerland |
| Series | Quantum Science and Technology |
| Izlaides gads | 2021 |
| Vāka tips | Cietais vāks |
| EAN | 9783030830977 |