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Data Mining : Practical Machine Learning Tools and Techniques by Christopher J.
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CircaEUR 36,37
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Oggetto che si trova a: Rockwall, Texas, Stati Uniti
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Numero oggetto eBay:197002759352
Specifiche dell'oggetto
- Condizione
- ISBN
- 9780128042915
Informazioni su questo prodotto
Product Identifiers
Publisher
Elsevier Science & Technology
ISBN-10
0128042915
ISBN-13
9780128042915
eBay Product ID (ePID)
227843028
Product Key Features
Number of Pages
654 Pages
Language
English
Publication Name
Data Mining : Practical Machine Learning Tools and Techniques
Subject
Management Information Systems, Intelligence (Ai) & Semantics, Databases / Data Mining, Databases / General
Publication Year
2016
Type
Textbook
Subject Area
Computers
Format
Trade Paperback
Dimensions
Item Length
9.2 in
Item Width
7.5 in
Additional Product Features
Edition Number
4
Intended Audience
College Audience
LCCN
2016-948470
Reviews
"...this volume is the most accessible introduction to data mining to appear in recent years. It is worthy of a fourth edition." --Computing Reviews
Dewey Edition
22
Illustrated
Yes
Dewey Decimal
006.3
Table Of Content
Part I: Introduction to data mining 1. What's it all about? 2. Input: Concepts, instances, attributes 3. Output: Knowledge representation 4. Algorithms: The basic methods 5. Credibility: Evaluating what's been learned Part II. More advanced machine learning schemes 6. Trees and rules 7. Extending instance-based and linear models 8. Data transformations 9. Probabilistic methods 10. Deep learning 11. Beyond supervised and unsupervised learning 12. Ensemble learning 13. Moving on: applications and beyond
Synopsis
Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches. Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including substantial new chapters on probabilistic methods and on deep learning. Accompanying the book is a new version of the popular WEKA machine learning software from the University of Waikato. Authors Witten, Frank, Hall, and Pal include today's techniques coupled with the methods at the leading edge of contemporary research. Please visit the book companion website at https: //www.cs.waikato.ac.nz/ ml/weka/book.html. It contains Powerpoint slides for Chapters 1-12. This is a very comprehensive teaching resource, with many PPT slides covering each chapter of the book Online Appendix on the Weka workbench; again a very comprehensive learning aid for the open source software that goes with the book Table of contents, highlighting the many new sections in the 4th edition, along with reviews of the 1st edition, errata, etc., Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches. Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including substantial new chapters on probabilistic methods and on deep learning. Accompanying the book is a new version of the popular WEKA machine learning software from the University of Waikato. Authors Witten, Frank, Hall, and Pal include today's techniques coupled with the methods at the leading edge of contemporary research. Please visit the book companion website at https://www.cs.waikato.ac.nz/~ml/weka/book.html. It contains Powerpoint slides for Chapters 1-12. This is a very comprehensive teaching resource, with many PPT slides covering each chapter of the book Online Appendix on the Weka workbench; again a very comprehensive learning aid for the open source software that goes with the book Table of contents, highlighting the many new sections in the 4th edition, along with reviews of the 1st edition, errata, etc., Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches. Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including substantial new chapters on probabilistic methods and on deep learning. Accompanying the book is a new version of the popular WEKA machine learning software from the University of Waikato. Authors Witten, Frank, Hall, and Pal include today's techniques coupled with the methods at the leading edge of contemporary research. Please visit the book companion website. It contains Powerpoint slides for Chapters 1-12. This is a very comprehensive teaching resource, with many PPT slides covering each chapter of the book Online Appendix on the Weka workbench; again a very comprehensive learning aid for the open source software that goes with the book Table of contents, highlighting the many new sections in the 4th edition, along with reviews of the 1st edition, errata, etc. Provides a thorough grounding in machine learning concepts, as well as practical advice on applying the tools and techniques to data mining projects Presents concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods Includes a downloadable WEKA software toolkit, a comprehensive collection of machine learning algorithms for data mining tasks-in an easy-to-use interactive interface Includes open-access online courses that introduce practical applications of the material in the book
LC Classification Number
QA76.9.D343W58 2017
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bbay1982
100% di Feedback positivi•88 oggetti venduti
Registrato come venditore privatoPertanto non si applicano i diritti dei consumatori derivanti dalla normativa europea. La Garanzia cliente eBay è comunque applicabile alla maggior parte degli acquisti. Scopri di piùScopri di più
Feedback sul venditore (33)
- i***c (194)- Feedback lasciato dall'acquirente.Ultimo annoAcquisto verificatoReally couldn’t recommend this seller enough. Super fast shipping . Packaging was great . As described. And really values the customer! Thanks again !Apple iPod Touch 4th Gen (A1367) - 64GB - Excellent Condition Tested Black (N° 197028766948)
- c***o (1245)- Feedback lasciato dall'acquirente.Ultimi 6 mesiAcquisto verificatoArrived very fast; as described. Good EBayer.OEM HLT-118A Hover-1 electric scooter Charger 42 Volts DSA-200 Replacement (N° 197028655607)
- e***s (57)- Feedback lasciato dall'acquirente.Ultimo annoAcquisto verificatoPackage arrived in time and was super secure in the box! Exactly as described and at a great deal. Seller even checked in occasionally during shipping to let me know what was happening:)insta 360 one (N° 196957519624)