Understanding Machine Learning Theory by Shwartz (27 results)

Condition: Very Good. Pages intact with possible writing/highlighting. Binding strong with minor wear. Dust jackets/supplements may not be included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

Paperback. Condition: NEW. International Edition, Brand New, ISBN and Cover same but contents similar to U.S. Edition, We ship from multiple Locations including India. Legal to use despite any disclaimer, We ship to PO , APO and FPO adresses in U.S.A. Ship from multiple Locations including India Choose Expedited Shipping for FASTER DELIVERY.Customer Satisfaction Guaranteed.…

Paperback. Condition: NEW. International Edition, Paperback, Brand New,ISBN and Cover image may differ but contents similar to U.S. Edition. We ship from multiple Locations including India, We ship to PO , APO and FPO adresses in U.S.A. Choose Expedited Shipping for FASTER DELIVERY.Customer Satisfaction Guaranteed.…

Paperback. Condition: Fair. First Edition. The item might be beaten up but readable. May contain markings or highlighting, as well as stains, bent corners, or any other major defect, but the text is not obscured in any way.

paperback. Condition: As New. Satisfaction guaranteed. Thank you.

Paperback. Condition: Good. 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.…

Paperback. Condition: Good. 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.…

Condition: very_good.

Condition: New. Brand New. Soft Cover International Edition. Different ISBN and Cover Image. Priced lower than the standard editions which is usually intended to make them more affordable for students abroad. The core content of the book is generally the same as the standard edition. The country selling restrictions may be printed on the book but is no problem for the self-use. This Item maybe shipped from US or any other country as we have multiple locations worldwide.…

Condition: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Condition: good. Book shows wear from use but remains a usable copy. May include writing highlighting underlining library markings. LISTING USES STOCK PHOTOS AND COVER MAY VARY. Ships via USPS and typically arrives within 10-12 business days.

Soft cover. Condition: New. ISBN:9781107512825.

Paperback. Condition: New. Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 6-10 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.…

Condition: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,1000grams, ISBN:9781107057135. …

Condition: good. Befriedigend/Good: Durchschnittlich erhaltenes Buch bzw. Schutzumschlag mit Gebrauchsspuren, aber vollständigen Seiten. / Describes the average WORN book or dust jacket that has all the pages present.

Condition: As New. Unread book in perfect condition.

Condition: New.

Condition: New. pp. 424 1st edition.

Condition: New.

Condition: New. Introduces machine learning and its algorithmic paradigms, explaining the principles behind automated learning approaches and the considerations underlying their usage. Num Pages: 409 pages, 47 b/w illus. 123 exercises. BIC Classification: UYQM. Category: (U) Tertiary Education (US: College). Dimension: 186 x 261 x 29. Weight in Grams: 912. . 2014. 1st Edition. Hardcover. . . . . …

Condition: As New. Unread book in perfect condition.

Condition: New. Introduces machine learning and its algorithmic paradigms, explaining the principles behind automated learning approaches and the considerations underlying their usage. Num Pages: 409 pages, 47 b/w illus. 123 exercises. BIC Classification: UYQM. Category: (U) Tertiary Education (US: College). Dimension: 186 x 261 x 29. Weight in Grams: 912. . 2014. 1st Edition. Hardcover. . . . . Books ship from the US and Ireland. …

Hardcover. Condition: Brand New. 397 pages. 10.00x7.00x1.00 inches. In Stock.

Hardcover. Condition: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Condition: New. Print on Demand pp. 424 47 Illus.

Condition: New. PRINT ON DEMAND pp. 424.

Hardback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.