Shwartz david (28 Ergebnisse)

Paperback. Zustand: Good. This edition is cleanly formatted for easy reading. 12 point Garamond, 1.25 spacing. For decades millions of people have learned the secrets of success through David J. Shwartz's The Magic of Thinking Big. Achieve financial advancement, work promotions, a positive outlook on life, fulfilling relationships, and lasting happiness. Aim high, and think BIG, and you will not only reach but surpass your goals, you will be a happier, bigger person with a bigger life.…

Hardcover. Zustand: Fair. No Jacket. Readable copy. Pages may have considerable notes/highlighting. ~ ThriftBooks: Read More, Spend Less.

Hardcover. Zustand: Fair. No Jacket. Readable copy. Pages may have considerable notes/highlighting. ~ ThriftBooks: Read More, Spend Less.

Hardcover. Zustand: Good. No Jacket. Missing dust jacket; Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.

Hardcover. Zustand: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.

Zustand: Good. Former library copy. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Includes library markings. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

Zustand: 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.

Zustand: 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. Zustand: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.

paperback. Zustand: Good. Most items will be dispatched the same or the next working day. A copy that has been read but remains in clean condition. All of the pages are intact and the cover is intact and the spine may show signs of wear. The book may have minor markings which are not specifically mentioned. A few small stains.…

Zustand: 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.

Zustand: As New. Unread book in perfect condition. Gould, David (illustrator).

Zustand: New. Gould, David (illustrator).

Paperback. Zustand: Brand New. 276 pages. 8.98x5.94x1.34 inches. In Stock.

Hardcover. Zustand: As New. No Jacket. Pages are clean and are not marred by notes or folds of any kind. ~ ThriftBooks: Read More, Spend Less.

Hardcover. Zustand: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.

Paperback. Zustand: Brand New. large type / large print edition edition. 348 pages. 9.68x7.44x0.79 inches. In Stock.

Hardcover. Zustand: New. Brand new book, sourced directly from publisher. Dispatch time is 24-48 hours from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

Hardback. Zustand: New. 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.…

Zustand: New.

Hardback. Zustand: New. 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.…

Zustand: As New. Unread book in perfect condition.

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

Zustand: New. 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 an.

Hardback. Zustand: New. 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.…

Hardback. Zustand: New. 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.…

Hardcover. Zustand: Good. Original decorated pictorial boards, banderole, numerous full page illustrations in colour and b/w, 1000 copies, text in English and Hebrew, unpaged, 8vo.; Back flap banderole folded.

Zustand: new. Pages: 436 Language: Russian. Mashinnoe obuchenie - odin iz samykh bystro razvivajuschikhsja razdelov informatiki, s prilozhenijami v samykh raznykh oblastjakh. Tsel etoj knigi - poznakomit chitatelja s fundamentalnymi printsipami mashinnogo obuchenija i kharakternymi dlja nego algoritmicheskimi paradigmami. Kniga soderzhit obshirnyj svod osnovopolagajuschikh teoreticheskikh idej mashinnogo obuchenija i matematicheskie vykladki, blagodarja kotorym eti idei stanovjatsja prakticheskimi algoritmami. Vsled za izlozheniem bazovykh osnov distsipliny rassmatrivaetsja shirokij spektr tem, ne nashedshikh dostatochnogo otrazhenija v predshestvujuschikh uchebnikakh: vychislitelnaja slozhnost obuchenija, ponjatija vypuklosti i ustojchivosti, vazhnye algoritmy, vkljuchaja stokhasticheskij gradientnyj spusk, nejronnye seti i obuchenie strukturirovannomu vyvodu, a takzhe sovsem nedavnie teoreticheskie kon. Rekomenduem! 9785970606735.…