Data science for dummies

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Bibliographic Details
Main Author Pierson, Lillian (Author)
Other Authors Porway, Jake (Author of introduction, etc.)
Format Book
LanguageEnglish
Published Hoboken : John Wiley & Sons, Inc., [2015]
Series--For dummies
Subjects
data
big data
analýza dat
zpracování dat
dolování dat
vizualizace (počítačová grafika)
data analysis
data processing
data mining
visualization (computer graphics)
příručky
handbooks, manuals, etc
ISBN9781118841556
Physical Descriptionxvi, 384 stran : ilustrace, grafy ; 24 cm

Cover

Table of Contents:
  • Part I: Getting Started With Data Science. Chapter 1: Wrapping Your Head around Data Science
  • Chapter 2: Exploring Data Engineering Pipelines and Infrastructure
  • Chapter 3: Applying Data Science to Business and Industry. Part II: Using Data Science to Extract Meaning from Your Data. Chapter 4: Introducing Probability and Statistics
  • Chapter 5: Clustering and Classification
  • Chapter 6: Clustering and Classification with Nearest Neighbor
  • Chapter 7: Mathematical Modeling in Data Science
  • Chapter 8: Modeling Spatial Data with Statistics. Part III: Creating Data Visualizations that Clearly Communicate. Chapter 9: Following the Principles of Data Visualization Design
  • Chapter 10: Using D3.js for Data Visualization
  • Chapter 11: Web-Based Applications for Visualization Design
  • Chapter 12: Exploring Best Practices in Dashboard Design
  • Chapter 13: Making Maps from Spatial Data. Part IV: Computing for Data Science. Chapter 14: Using Python for Data Science
  • Chapter 15: Using Open Source R for Data Science
  • Chapter 16: Using SQL in Data Science
  • Chapter 17: Software Applications for Data Science. Part V: Applying Domain Expertise to Solve Real-World Problems. Chapter 18: Using Data Science in Journalism
  • Chapter 19: Delving into Environmental Data Science
  • Chapter 20: Data Science for Driving Growth in E-Commerce
  • Chapter 21: Using Data Science to Describe and Predict Criminal Activity. Part VI: The Part of Tens. Chapter 22: Ten Phenomenal Resources for Open Data
  • Chapter 23: Ten (or So) Free Data Science Tools and Applications

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