• Data Science for dummies
  • 點閱:16
  • 作者: by Lillian Pierson
  • 出版社:John Wiley & Sons
  • 出版年:c2015
  • 集叢名:--For dummies
  • ISBN:9781118841556 ; 9781118841457
  • 格式:PDF
  • 版次:1st ed.

Data Science For Dummies begins by explaining large data sets and data formats, including sample Python code for manipulating data. The book explains how to work with relational databases and unstructured data, including NoSQL. The book then moves into preparing data for analysis by cleaning it up, or 'munging' it. From there the book explains data visualization techniques and types of data sets. Part II of the book is all about supervised machine learning, including regression techniques and model validation techniques. Part III explains unsupervised machine learning, including clustering and recommendation engines. Part IV overviews big data processing, including MapReduce, Hadoop, Dremel, Storm, and Spark. The book finishes up with real world applications of data science and how data science fits into organizations.

  • Foreword(第xv頁)
  • Introduction(第1頁)
    • About This Book(第2頁)
    • Foolish Assumptions(第2頁)
    • Icons Used in This Book(第2頁)
    • Beyond the Book(第3頁)
    • Where to Go from Here(第3頁)
  • Part I Getting Started With Data Science(第5頁)
    • Chapter 1 Wrapping Your Head around Data Science(第7頁)
    • Chapter 2 Exploring Data Engineering Pipelines and Infrastructure(第17頁)
    • Chapter 3 Applying Data Science to Business and Industry(第33頁)
  • Part II Using Data Science to Extract Meaning from Your Data(第47頁)
    • Chapter 4 Introducing Probability and Statistics(第49頁)
    • Chapter 5 Clustering and Classification(第73頁)
    • Chapter 6 Clustering and Classification with Nearest Neighbor Algorithms(第87頁)
    • Chapter 7 Mathematical Modeling in Data Science(第99頁)
    • Chapter 8 Modeling Spatial Data with Statistics(第113頁)
  • Part III Creating Data Visualizations that Clearly Communicate Meaning(第129頁)
    • Chapter 9 Following the Principles of Data Visualization Design(第131頁)
    • Chapter 10 Using D3.js for Data Visualization(第157頁)
    • Chapter 11 Web-Based Applications for Visualization Design(第171頁)
    • Chapter 12 Exploring Best Practices in Dashboard Design(第189頁)
    • Chapter 13 Making Maps from Spatial Data(第195頁)
  • Part IV Computing for Data Science(第215頁)
    • Chapter 14 Using Python for Data Science(第217頁)
    • Chapter 15 Using Open Source R for Data Science(第239頁)
    • Chapter 16 Using SQL in Data Science(第255頁)
    • Chapter 17 Software Applications for Data Science(第267頁)
  • Part V Applying Domain Expertise to Solve Real-World Problems Using Data Science(第279頁)
    • Chapter 18 Using Data Science in Journalism(第281頁)
    • Chapter 19 Delving into Environmental Data Science(第299頁)
    • Chapter 20 Data Science for Driving Growth in E-Commerce(第311頁)
    • Chapter 21 Using Data Science to Describe and Predict Criminal Activity(第327頁)
  • Part VI The Part of Tens(第337頁)
    • Chapter 22 Ten Phenomenal Resources for Open Data(第339頁)
    • Chapter 23 Ten (or So) Free Data Science Tools and Applications(第351頁)
  • Index(第365頁)
紙本書 NT$ 960
NT$ 672

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