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Data Mining For Dummies [electronic resource] / Brown, Meta S..

By: Call Number: Ebook Material type: TextLanguage: English Publication details: WILEY, 2014.Description: 412 pISBN:
  • 9781118893173
  • 9781118893197
Subject(s): Online resources:
Contents:
Chapter, Lesson, Part Part I: Getting Started with Data Mining.
Chapter, Lesson, Part Chapter 1: Catching the Data-Mining Train.
Chapter, Lesson, Part Chapter 2: A Day in Your Life as a Data Miner.
Chapter, Lesson, Part Chapter 3: Teaming Up to Reach Your Goals.
Chapter, Lesson, Part Part II: Exploring Data-Mining Mantras and Methods.
Chapter, Lesson, Part Chapter 4: Learning the Laws of Data Mining.
Chapter, Lesson, Part Chapter 5: Embracing the Data-Mining Process.
Chapter, Lesson, Part Chapter 6: Planning for Data-Mining Success.
Chapter, Lesson, Part Chapter 7: Gearing Up with the Right Software.
Chapter, Lesson, Part Part III: Gathering the Raw Materials.
Chapter, Lesson, Part Chapter 8: Digging into Your Data.
Chapter, Lesson, Part Chapter 9: Making New Data.
Chapter, Lesson, Part Chapter 10: Ferreting Out Public Data Sources.
Chapter, Lesson, Part Chapter 11: Buying Data.
Chapter, Lesson, Part Part IV: A Data Miner's Survival Kit.
Chapter, Lesson, Part Chapter 12: Getting Familiar with Your Data.
Chapter, Lesson, Part Chapter 13: Dealing in Graphic Detail.
Chapter, Lesson, Part Chapter 14: Showing Your Data Who's Boss.
Chapter, Lesson, Part Chapter 15: Your Exciting Career in Modeling.
Chapter, Lesson, Part Part V: More Data-Mining Methods.
Chapter, Lesson, Part Chapter 16: Data Mining Using Classic Statistical Methods.
Chapter, Lesson, Part Chapter 17: Mining Data for Clues.
Chapter, Lesson, Part Chapter 18: Expanding Your Horizons.
Chapter, Lesson, Part Part VI: The Part of Tens.
Chapter, Lesson, Part Chapter 19: Ten Great Resources for Data Miners.
Chapter, Lesson, Part Chapter 20: Ten Useful Kinds of Analysis That Complement Data Mining.
Cover, Title,Verse : an introduction to prosody--Preface, Introduction, TOC,Contents at a Glance--Preface, Introduction, TOC,Table of Contents--Preface, Introduction, TOC,Introduction--References, Appendix, Index,Appendix A: Glossary--References, Appendix, Index,Appendix B: Data-Mining Sof tware Sources--References, Appendix, Index,Appendix C: Major Data Vendors--References, Appendix, Index,Appendix D: Sources and Citations--References, Appendix, Index,Index--References, Appendix, Index,About the Author.
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Chapter, Lesson, Part Part I: Getting Started with Data Mining.

Chapter, Lesson, Part Chapter 1: Catching the Data-Mining Train.

Chapter, Lesson, Part Chapter 2: A Day in Your Life as a Data Miner.

Chapter, Lesson, Part Chapter 3: Teaming Up to Reach Your Goals.

Chapter, Lesson, Part Part II: Exploring Data-Mining Mantras and Methods.

Chapter, Lesson, Part Chapter 4: Learning the Laws of Data Mining.

Chapter, Lesson, Part Chapter 5: Embracing the Data-Mining Process.

Chapter, Lesson, Part Chapter 6: Planning for Data-Mining Success.

Chapter, Lesson, Part Chapter 7: Gearing Up with the Right Software.

Chapter, Lesson, Part Part III: Gathering the Raw Materials.

Chapter, Lesson, Part Chapter 8: Digging into Your Data.

Chapter, Lesson, Part Chapter 9: Making New Data.

Chapter, Lesson, Part Chapter 10: Ferreting Out Public Data Sources.

Chapter, Lesson, Part Chapter 11: Buying Data.

Chapter, Lesson, Part Part IV: A Data Miner's Survival Kit.

Chapter, Lesson, Part Chapter 12: Getting Familiar with Your Data.

Chapter, Lesson, Part Chapter 13: Dealing in Graphic Detail.

Chapter, Lesson, Part Chapter 14: Showing Your Data Who's Boss.

Chapter, Lesson, Part Chapter 15: Your Exciting Career in Modeling.

Chapter, Lesson, Part Part V: More Data-Mining Methods.

Chapter, Lesson, Part Chapter 16: Data Mining Using Classic Statistical Methods.

Chapter, Lesson, Part Chapter 17: Mining Data for Clues.

Chapter, Lesson, Part Chapter 18: Expanding Your Horizons.

Chapter, Lesson, Part Part VI: The Part of Tens.

Chapter, Lesson, Part Chapter 19: Ten Great Resources for Data Miners.

Chapter, Lesson, Part Chapter 20: Ten Useful Kinds of Analysis That Complement Data Mining.

Cover, Title,Verse : an introduction to prosody--Preface, Introduction, TOC,Contents at a Glance--Preface, Introduction, TOC,Table of Contents--Preface, Introduction, TOC,Introduction--References, Appendix, Index,Appendix A: Glossary--References, Appendix, Index,Appendix B: Data-Mining Sof tware Sources--References, Appendix, Index,Appendix C: Major Data Vendors--References, Appendix, Index,Appendix D: Sources and Citations--References, Appendix, Index,Index--References, Appendix, Index,About the Author.

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