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Condition: very_good. Gently read. May have name of previous ownership, or ex-library edition. Binding tight; spine straight and smooth, with no creasing; covers clean and crisp. Minimal signs of handling or shelving. 100% GUARANTEE! Shipped with delivery confirmation, if you're not satisfied with purchase please return item! Ships USPS Media Mail.
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paperback. Condition: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
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Paperback. Condition: Very Good. Connecting readers with great books since 1972! Used books may not include companion materials, and may have some shelf wear or limited writing. We ship orders daily and Customer Service is our top priority!
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Paperback. Condition: Very Good. Connecting readers with great books since 1972! Used books may not include companion materials, and may have some shelf wear or limited writing. We ship orders daily and Customer Service is our top priority!
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Condition: As New. Unread book in perfect condition.
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PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.
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Condition: New.
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PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.
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Parallel R: Data Analysis in the Distributed World (Paperback or Softback)
Language: English
Published by O'Reilly Media 11/5/2011, 2011
ISBN 10: 1449309925 ISBN 13: 9781449309923
Paperback or Softback. Condition: New. Parallel R: Data Analysis in the Distributed World. Book.
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International EditionPaperback. 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.
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International Edition
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.
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Condition: As New. Unread book in perfect condition.
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Condition: New.
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Parallel R
Language: English
Published by O'Reilly Media, Inc, USA, 2011
ISBN 10: 1449309925 ISBN 13: 9781449309923
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Seller rating 5 out of 5 stars
Paperback / softback. Condition: New. New copy - Usually dispatched within 4 working days.
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Condition: As New. Unread book in perfect condition.
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Parallel R
Seller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Ireland
Seller rating 5 out of 5 stars
Condition: New. R is a wonderful thing, indeed: in recent years this free, open-source product has become a popular toolkit for statistical analysis and programming. Two of R's limitations -- that it is single-threaded and memory-bound -- become especially troublesome in the current era of large-scale data analysis. Num Pages: 122 pages, Illustrations. BIC Classification: UMX. Category: (XV) Technical / Manuals. Dimension: 233 x 178 x 8. Weight in Grams: 244. . 2011. Paperback. . . . .
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Paperback. Condition: New. Illustrated. Welcome to data science's dirty secret: real-world data is messy. Data scientists must spend a good deal of time playing software developer, writing code to clean up data before they can actually do anything constructive with it. It's a necessary evil, but you can still make the most of it. This practical book walks you through several real-world examples to demonstrate the theory and practice behind working with and cleaning up dirty data. No one tool solves all of the problems well. Wise data scientists learn many tools and learn where each one shines. To that end, this book takes a polyglot approach: most examples will involve R and Python, but expect the occasional smattering of Groovy and sed/awk fun.
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Condition: New. R is a wonderful thing, indeed: in recent years this free, open-source product has become a popular toolkit for statistical analysis and programming. Two of R's limitations -- that it is single-threaded and memory-bound -- become especially troublesome in the current era of large-scale data analysis. Num Pages: 122 pages, Illustrations. BIC Classification: UMX. Category: (XV) Technical / Manuals. Dimension: 233 x 178 x 8. Weight in Grams: 244. . 2011. Paperback. . . . . Books ship from the US and Ireland.
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Bad Data Handbook : Cleaning Up the Data So You Can Get Back to Work
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: New.
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Bad Data Handbook : Cleaning Up the Data So You Can Get Back to Work
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: As New. Unread book in perfect condition.
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Bad Data Handbook: Cleaning Up the Data So You Can Get Back to Work (Paperback or Softback)
Language: English
Published by O'Reilly Media 11/24/2012, 2012
ISBN 10: 1449321887 ISBN 13: 9781449321888
Paperback or Softback. Condition: New. Bad Data Handbook: Cleaning Up the Data So You Can Get Back to Work. Book.
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Bad Data Handbook: Cleaning Up the Data So You Can Get Back to Work
Language: English
Published by O'Reilly Media, Inc, USA, 2012
ISBN 10: 1449321887 ISBN 13: 9781449321888
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Seller rating 5 out of 5 stars
Paperback / softback. Condition: New. New copy - Usually dispatched within 4 working days.
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Blanda. Condition: New. Dust Jacket Condition: Nuevo. No Aplica (illustrator). 1. It?s tough to argue with R as a high-quality, cross-platform, open source statistical software product?unless you?re in the business of crunching Big Data. This concise book introduces you to several strategies for using R to analyze large datasets, including three chapters on using R and Hadoop together. You?ll learn the basics of Snow, Multicore, Parallel, Segue, RHIPE, and Hadoop Streaming, including how to find them, how to use them, when they work well, and when they don?t. With these packages, you can overcome R?s single-threaded nature by spreading work across multiple CPUs, or offloading work to multiple machines to address R?s memory barrier. Snow: works well in a traditional cluster environment. Multicore: popular for multiprocessor and multicore computers. Parallel: part of the upcoming R 2.14.0 release. R+Hadoop: provides low-level access to a popular form of cluster computing. RHIPE: uses Hadoop?s power with R?s language and interactive shell. Segue: lets you use Elastic MapReduce as a backend for lapply-style operations. 240 gr. Libro.
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Bad Data Handbook: Cleaning Up the Data So You Can Get Back to Work
Language: English
Published by Oreilly & Associates Inc, 2012
ISBN 10: 1449321887 ISBN 13: 9781449321888
Paperback. Condition: Brand New. 1st edition. 245 pages. 9.25x6.75x0.75 inches. In Stock.
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Parallel R
Language: English
Published by O'Reilly Media, Inc., 2011
ISBN 10: 1449309925 ISBN 13: 9781449309923
Kartoniert / Broschiert. Condition: New. R is a wonderful thing, indeed: in recent years this free, open-source product has become a popular toolkit for statistical analysis and programming. Two of R s limitations -- that it is single-threaded and memory-bound -- become especially troublesome in .
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paperback. Condition: New. In shrink wrap. Looks like an interesting title!
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Paperback. Condition: New. Illustrated. Welcome to data science's dirty secret: real-world data is messy. Data scientists must spend a good deal of time playing software developer, writing code to clean up data before they can actually do anything constructive with it. It's a necessary evil, but you can still make the most of it. This practical book walks you through several real-world examples to demonstrate the theory and practice behind working with and cleaning up dirty data. No one tool solves all of the problems well. Wise data scientists learn many tools and learn where each one shines. To that end, this book takes a polyglot approach: most examples will involve R and Python, but expect the occasional smattering of Groovy and sed/awk fun.
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Condition: New. Welcome to data science s dirty secret: real-world data is messy. Data scientists must spend a good deal of time playing software developer, writing code to clean up data before they can actually do anything constructive with it. This is a necessary evil, b.
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Parallel R
Language: English
Published by O'Reilly Media, Inc, USA, 2011
ISBN 10: 1449309925 ISBN 13: 9781449309923
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Seller rating 5 out of 5 stars
£ 21.05
£ 15.75 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketPaperback / softback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
