Minggu, 21 Juli 2013

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THE RUSSIAN’S PROPOSITION: 3

He pushes her limits…but how can she say no to the man who’d kill for her?

Bent on revenge, sexy Russian mobster Viktor Kozlov sets out to kill the criminal who kidnapped and tortured his beloved submissive Eva. But when his trust is betrayed and a secret alliance is revealed, Eva is imperiled. The curvy, sexy baker-turned-mob-mistress must outwit the conspirator and warn her master of the impending danger. After the bullets fly, Eva and Viktor retreat to The Underground, the famed BDSM sex club to establish their alibi. But can she prove herself to be his match—in bed—and out of it?

Reader Advisory: This is the third and final 10,000 word installment of a dark BDSM romance serial about the Russian Mafia. It contains explicit scenes of dominance, submission, bondage, violence, anal sex, dark kink and taboo acts. For adults only.

  • Sales Rank: #775142 in eBooks
  • Published on: 2015-07-26
  • Released on: 2015-07-26
  • Format: Kindle eBook

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0 of 0 people found the following review helpful.
Viktoria and Eva - true love!!
By Raymis
Would love to meet the author behind the hottest, sexy and best erotic books out there!! Love the Russian mob love stories and how the whole series connects with her other Russian characters!! Must read!!!!! You won't be disappointed if you are looking for something hot, quick, sexy and fulfilling!!!

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Jumat, 19 Juli 2013

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  • Published on: 2014-01-04
  • Binding: Hardcover

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Rabu, 17 Juli 2013

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Clifford's Big Dictionary, by Scholastic

The perfect back-to-school reference book for the early elementary set!

From Scholastic, the most trusted name in learning (R), comes this picture dictionary featuring America's favorite big red dog, Clifford!

The 128-page dictionary has:
* Alphabetical entries, with 10-25 words per letter, each illustrated with spot art.
* Simple sentences beneath each word to help describe it and put it in context.
* Frontmatter and backmatter, which includes sections on how to use a dictionary, numbers & colors, opposites, the body, things that go, Clifford's Big Ideas, and more!

  • Sales Rank: #282996 in Books
  • Brand: Cartwheel
  • Published on: 2011-07-01
  • Original language: English
  • Number of items: 1
  • Dimensions: 11.25" h x 8.75" w x .50" l, 1.64 pounds
  • Binding: Hardcover
  • 128 pages

Most helpful customer reviews

0 of 0 people found the following review helpful.
Excellent first dictionary for childdren
By B. Nelson
This is a great book for children who are learning to read. The colors are great for children and the book is filled with pictures that keep the attention of the child. The pictures are filled with humor and variety that add to the interest of the text.The words are easy but practical for a beginning learner. Extremely well done book that is an asset for the early learner and for the beginning self learner. This is an outstanding first dictionary book for young children.

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Great book to increase your child's vocabulary
By FunFamily
Lots of great words for kids. The illustrations are colorful and matches well with the word and definition. This books keeps our child engaged for a good amount of time.

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Cliffords big dictionary
By andrew
book was in decent shape it had pages that where riped but had been taped. Concept of book is great for small children.

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Kamis, 11 Juli 2013

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Predicting Structured Data (Neural Information Processing series)From The MIT Press

Machine learning develops intelligent computer systems that are able to generalize from previously seen examples. A new domain of machine learning, in which the prediction must satisfy the additional constraints found in structured data, poses one of machine learning's greatest challenges: learning functional dependencies between arbitrary input and output domains. This volume presents and analyzes the state of the art in machine learning algorithms and theory in this novel field. The contributors discuss applications as diverse as machine translation, document markup, computational biology, and information extraction, among others, providing a timely overview of an exciting field.

Contributors Yasemin Altun, Gökhan Bakir, Olivier Bousquet, Sumit Chopra, Corinna Cortes, Hal Daumé III, Ofer Dekel, Zoubin Ghahramani, Raia Hadsell, Thomas Hofmann, Fu Jie Huang, Yann LeCun, Tobias Mann, Daniel Marcu, David McAllester, Mehryar Mohri, William Stafford Noble, Fernando Pérez-Cruz, Massimiliano Pontil, Marc'Aurelio Ranzato, Juho Rousu, Craig Saunders, Bernhard Schölkopf, Matthias W. Seeger, Shai Shalev-Shwartz, John Shawe-Taylor, Yoram Singer, Alexander J. Smola, Sandor Szedmak, Ben Taskar, Ioannis Tsochantaridis, S.V.N Vishwanathan, Jason Weston.

  • Sales Rank: #1955208 in Books
  • Published on: 2007-07-27
  • Original language: English
  • Number of items: 1
  • Dimensions: 10.00" h x .63" w x 8.00" l, 1.94 pounds
  • Binding: Hardcover
  • 360 pages

About the Author
Gökhan Bakir is Research Scientist at the Max Planck Institute for Biological Cybernetics in Tübingen, Germany.

Thomas Hofmann is a Director of Engineering at Google's Engineering Center in Zurich and Adjunct Associate Professor of Computer Science at Brown University.

Bernhard Schölkopf is Professor and Director at the Max Planck Institute for Biological Cybernetics in Tübingen, Germany. He is coauthor of Learning with Kernels (2002) and is a coeditor of Advances in Kernel Methods: Support Vector Learning (1998), Advances in Large-Margin Classifiers (2000), and Kernel Methods in Computational Biology (2004), all published by the MIT Press.

Alexander J. Smola is Senior Principal Researcher and Machine Learning Program Leader at National ICT Australia/Australian National University, Canberra.

Ben Taskar is Assistant Professor in the Computer and Information Science Department at the University of Pennsylvania.

S. V. N. Vishwanathan is an Assistant Professor of Statistics and Computer Science at Purdue University and Senior Researcher in the Statistical Machine Learning Program, National ICT Australia with an adjunct appointment at the Research School for Information Sciences and Engineering, Australian National University.

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