Understanding Machine Learning by Shai Shalev-Shwartz: Used

AlibrisBooks
(496300)
Venditore professionale
Registrato come venditore professionale
US $45,33
CircaEUR 39,29
Condizione:
Buone condizioni
Goditi i vantaggi. Restituzioni accettate.
Spedizione:
Gratis Standard Shipping.
Oggetto che si trova a: Sparks, Nevada, Stati Uniti
Consegna:
Consegna prevista tra il lun 24 nov e il sab 29 nov a 94104
I tempi di consegna previsti utilizzando il metodo proprietario di eBay, che è basato sulla vicinanza dell'acquirente rispetto al luogo in cui si trova l'oggetto, sul servizio di spedizione selezionato, sulla cronologia di spedizione del venditore e su altri fattori. I tempi di consegna possono variare, specialmente durante le festività.
Restituzioni:
Restituzioni entro 30 giorni. Le spese di spedizione del reso sono a carico dell'acquirente..
Pagamenti:
    Diners Club

Fai shopping in tutta sicurezza

Garanzia cliente eBay
Se non ricevi l'oggetto che hai ordinato, riceverai il rimborso. Scopri di piùGaranzia cliente eBay - viene aperta una nuova finestra o scheda
Il venditore si assume la piena responsabilità della messa in vendita dell'oggetto.
Numero oggetto eBay:403944431116
Ultimo aggiornamento: 20 nov 2025 00:19:49 CETVedi tutte le revisioniVedi tutte le revisioni

Specifiche dell'oggetto

Condizione
Buone condizioni: Libro che è già stato letto ma è in buone condizioni. Mostra piccolissimi danni ...
Book Title
Understanding Machine Learning
Publication Date
2014-05-19
Pages
410
ISBN
9781107057135
Categoria

Informazioni su questo prodotto

Product Identifiers

Publisher
Cambridge University Press
ISBN-10
1107057132
ISBN-13
9781107057135
eBay Product ID (ePID)
171820749

Product Key Features

Number of Pages
410 Pages
Publication Name
Understanding Machine Learning : from Theory to Algorithms
Language
English
Publication Year
2014
Subject
Algebra / General, Computer Vision & Pattern Recognition
Type
Textbook
Subject Area
Mathematics, Computers
Author
Shai Ben-David, Shai Shalev-Shwartz
Format
Hardcover

Dimensions

Item Height
1.1 in
Item Weight
32.2 Oz
Item Length
10.2 in
Item Width
7.2 in

Additional Product Features

Intended Audience
Scholarly & Professional
LCCN
2014-001779
Reviews
Advance praise: 'This elegant book covers both rigorous theory and practical methods of machine learning. This makes it a rather unique resource, ideal for all those who want to understand how to find structure in data.' Bernhard Schölkopf, Max Planck Institute for Intelligent Systems, "This elegant book covers both rigorous theory and practical methods of machine learning. This makes it a rather unique resource, ideal for all those who want to understand how to find structure in data." Bernhard Schlkopf, Max Planck Institute for Intelligent Systems
Dewey Edition
23
Illustrated
Yes
Dewey Decimal
006.3/1
Table Of Content
1. Introduction; Part I. Foundations: 2. A gentle start; 3. A formal learning model; 4. Learning via uniform convergence; 5. The bias-complexity trade-off; 6. The VC-dimension; 7. Non-uniform learnability; 8. The runtime of learning; Part II. From Theory to Algorithms: 9. Linear predictors; 10. Boosting; 11. Model selection and validation; 12. Convex learning problems; 13. Regularization and stability; 14. Stochastic gradient descent; 15. Support vector machines; 16. Kernel methods; 17. Multiclass, ranking, and complex prediction problems; 18. Decision trees; 19. Nearest neighbor; 20. Neural networks; Part III. Additional Learning Models: 21. Online learning; 22. Clustering; 23. Dimensionality reduction; 24. Generative models; 25. Feature selection and generation; Part IV. Advanced Theory: 26. Rademacher complexities; 27. Covering numbers; 28. Proof of the fundamental theorem of learning theory; 29. Multiclass learnability; 30. Compression bounds; 31. PAC-Bayes; Appendix A. Technical lemmas; Appendix B. Measure concentration; Appendix C. Linear algebra.
Synopsis
Machine learning is one of the fastest growing areas of computer science, with far-reaching applications. The aim of this textbook is to introduce machine learning, and the algorithmic paradigms it offers, in a principled way. The book provides an extensive theoretical account of the fundamental ideas underlying machine learning and the mathematical derivations that transform these principles into practical algorithms. Following a presentation of the basics of the field, the book covers a wide array of central topics that have not been addressed by previous textbooks. These include a discussion of the computational complexity of learning and the concepts of convexity and stability; important algorithmic paradigms including stochastic gradient descent, neural networks, and structured output learning; and emerging theoretical concepts such as the PAC-Bayes approach and compression-based bounds. Designed for an advanced undergraduate or beginning graduate course, the text makes the fundamentals and algorithms of machine learning accessible to students and non-expert readers in statistics, computer science, mathematics, and engineering., Machine learning is one of the fastest growing areas of computer science, with far-reaching applications. The aim of this textbook is to introduce machine learning, and the algorithmic paradigms it offers, in a principled way. The book provides a theoretical account of the fundamentals underlying machine learning and the mathematical derivations that transform these principles into practical algorithms. Following a presentation of the basics, the book covers a wide array of central topics unaddressed by previous textbooks. These include a discussion of the computational complexity of learning and the concepts of convexity and stability; important algorithmic paradigms including stochastic gradient descent, neural networks, and structured output learning; and emerging theoretical concepts such as the PAC-Bayes approach and compression-based bounds. Designed for advanced undergraduates or beginning graduates, the text makes the fundamentals and algorithms of machine learning accessible to students and non-expert readers in statistics, computer science, mathematics and engineering., Machine learning is one of the fastest growing areas of computer science, with far-reaching applications. This book explains the principles behind the automated learning approach and the considerations underlying its usage. The authors explain the 'hows' and 'whys' of machine-learning algorithms, making the field accessible to both students and practitioners.
LC Classification Number
Q325.5 .S475 2014

Descrizione dell'oggetto fatta dal venditore

Informazioni sul venditore professionale

Certifico che tutte le mie attività di vendita saranno conformi alle leggi e ai regolamenti dell'Unione europea.
Numeri relativi alla responsabilità estesa del produttore (EPR):
Il numero EPR indica che il venditore è registrato presso gli uffici governativi come produttore di un determinato tipo di prodotto e si assume la responsabilità di gestire i rifiuti generati da tale prodotto.

Informazioni su questo venditore

AlibrisBooks

99,1% di Feedback positivi2,0 milioni oggetti venduti

Su eBay da mag 2008
In genere risponde entro 24 ore
Registrato come venditore professionale
Alibris is the premier online marketplace for independent sellers of new & used books, as well as rare & collectible titles. We connect people who love books to thousands of independent sellers around ...
Mostra altro

Valutazione dettagliata del venditore

Media degli ultimi 12 mesi
Descrizione
4.9
Spese spedizione
5.0
Tempi di spedizione
5.0
Comunicazione
5.0

Feedback sul venditore (551.243)

Tutti i punteggiselected
Positivo
Neutro
Negativo
  • r***g (242)- Feedback lasciato dall'acquirente.
    Mese scorso
    Acquisto verificato
    Book was "nearly new" and "as described" in listing. The advertised price was fair and a good value. Unfortunately, the seller's shipping partner was very slow to get the book packaged and shipped. Shipping took too long, and the tracking info gave no reliable info on shipping date, time in transit or expected delivery. Seller did everything right, but their shipping partner needs improvement. I recommend this seller to other eBay buyers....... just make sure you're okay with the shipping terms.
  • e***u (283)- Feedback lasciato dall'acquirente.
    Mese scorso
    Acquisto verificato
    The listing was for a hardcover version of this book; however, I received a paperback. The Seller replied quickly to my question about this issue and issued a full refund - and let me keep the book. So, a diligent Seller for sure - and well packaged and reasonable timing on shipping. Thank you for the refund, and as you suggested, I'll likely donate this volume and seek the hardcover.
  • e***n (392)- Feedback lasciato dall'acquirente.
    Ultimi 6 mesi
    Acquisto verificato
    Great transaction, exactly as described, packed well, and promptly shipped on August 6th. Unfortunately the U.S. Postal Service took 23 calendar days to deliver the book. It was shipped from Pennsylvania, to Atlanta, past Alabama to Texas, enjoyed several days in Texas, then to Minneapolis, Jacksonville, Florida, back to Atlanta, finally to Birmingham, and Huntsville. The seller was very responsive and I decided it was interesting to see if/how the book would arrive. Thanks, Joe