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Thinking Of You - The Ultimate Escapist Read
Jill Mansell, unlike other writers in the rom-com arena, seems to get better with every book she writes. Thinking of You is her latest offering and proves that it is possible to get better with age!



Ginny Holland, a best selling author if left rattling around in her house on her own after daughter Jem goes to university. Lonely, she advertises her spare room for rent. Instead of a happy roommate, she gets moaning Laurel who is still hung up on her ex-boyfriend. If that wasn’t enough, Ginny finds herself lusting after two men who can only be bad for her. Will Ginny get the man of her dreams, or will he be the one that gets away?



Mansell has a disarming ability to create characters that you already know and that tends to make her books impossible to put down. This book is no different. It is charmingly written, hopelessly funny and will make you forget all of your own troubles as soon as you read the first page.


(ISBN: 0755328116, ISBN-13: 9780755328116)



Book Price comparison of Thinking Of You



Title: Data Mining: Know It All
Author: Ian H. Witten
ISBN: 0123746299
EAN: 9780123746290
496 Pages
Publisher: Morgan Kaufmann
Binding: Hardcover
Publication date: 2009-01-02


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Book Data Mining: Know It All on Amazon UK Buy nowNEW£ 33.24free on orders over £ 19£ 33.24Buy now
Blackwell - Buy NowNEW£ 34.99free on orders over £ 20£ 34.99Buy now
Book Data Mining: Know It All new from BooksellerNEW£ 33.24£ 2.75£ 35.99Buy now
USED*£ 50.81starting at £2.40£ 53.21Buy now

This book brings all of the elements of data mining together in a single volume, saving the reader the time and expense of making multiple purchases. It consolidates both introductory and advanced topics, thereby covering the gamut of data mining and machine learning tactics ? from data integration and pre-processing, to fundamental algorithms, to optimization techniques and web mining methodology.

The proposed book expertly combines the finest data mining material from the Morgan Kaufmann portfolio. Individual chapters are derived from a select group of MK books authored by the best and brightest in the field. These chapters are combined into one comprehensive volume in a way that allows it to be used as a reference work for those interested in new and developing aspects of data mining.

This book represents a quick and efficient way to unite valuable content from leading data mining experts, thereby creating a definitive, one-stop-shopping opportunity for customers to receive the information they would otherwise need to round up from separate sources.

* Chapters contributed by various recognized experts in the field let the reader remain up to date and fully informed from multiple viewpoints.

* Presents multiple methods of analysis and algorithmic problem-solving techniques, enhancing the readers technical expertise and ability to implement practical solutions.

* Coverage of both theory and practice brings all of the elements of data mining together in a single volume, saving the reader the time and expense of making multiple purchases.
This book brings all of the elements of data mining together in a single volume, saving the reader the time and expense of making multiple purchases. It consolidates both introductory and advanced topics, thereby covering the gamut of data mining and machine learning tactics from data integration and pre-processing, to fundamental algorithms, to optimization techniques and web mining methodology. The proposed book expertly combines the finest data mining material from the Morgan Kaufmann portfolio. Individual chapters are derived from a select group of MK books authored by the best and brightest in the field.These chapters are combined into one comprehensive volume in a way that allows it to be used as a reference work for those interested in new and developing aspects of data mining. This book represents a quick and efficient way to unite valuable content from leading data mining experts, thereby creating a definitive, one-stop-shopping opportunity for customers to receive the information they would otherwise need to round up from separate sources.

Chapters contributed by various recognized experts in the field let the reader remain up to date and fully informed from multiple viewpoints. This book presents multiple methods of analysis and algorithmic problem-solving techniques, enhancing the readers technical expertise and ability to implement practical solutions. Its coverage of both theory and practice brings all of the elements of data mining together in a single volume, saving the reader the time and expense of making multiple purchases.

Ian H. Witten is a professor of computer science at the University of Waikato in New Zealand. He directs the New Zealand Digital Library research project. His research interests include information retrieval, machine learning, text compression, and programming by demonstration. He received an MA in Mathematics from Cambridge University, England; an MSc in Computer Science from the University of Calgary, Canada; and a PhD in Electrical Engineering from Essex University, England. He is a fellow of the ACM and of the Royal Society of New Zealand. He has published widely on digital libraries, machine learning, text compression, hypertext, speech synthesis and signal processing, and computer typography. He has written several books, the latest being
Managing Gigabytes (1999) and Data Mining (2000), both from Morgan Kaufmann.


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