Data Science For Dummies

Editorial Reviews

Discover how data science can help you gain in-depth insightinto your business – the easy way!

Jobs in data science abound, but few people have the datascience skills needed to fill these increasingly important roles inorganizations. Data Science For Dummies is the perfectstarting point for IT professionals and students interested inmaking sense of their organization’s massive data sets andapplying their findings to real-world business scenarios. Fromuncovering rich data sources to managing large amounts of datawithin hardware and software limitations, ensuring consistency inreporting, merging various data sources, and beyond, you’lldevelop the know-how you need to effectively interpret data andtell a story that can be understood by anyone in yourorganization. * Provides a background in data science fundamentals beforemoving on to working with relational databases and unstructureddata and preparing your data for analysis * Details different data visualization techniques that can beused to showcase and summarize your data * Explains both supervised and unsupervised machine learning,including regression, model validation, and clusteringtechniques * Includes coverage of big data processing tools like MapReduce,Hadoop, Dremel, Storm, and Spark

It’s a big, big data world out there – let DataScience For Dummies help you harness its power and gain acompetitive edge for your organization.

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
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

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

Book Details

  • Author:
  • Pages: 408 pages
  • Edition: 1
  • Publication Date: 2015-03-16
  • Publisher:
  • Language: English
  • ISBN-10: 1118841557
  • ISBN-13: 9781118841556

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