Title:
Data science for dummies
Author:
Pierson, Lillian author.
ISBN:
9781118841556
Personal Author:
Physical Description:
xvi, 384 pages : illustrations, charts ; 24 cm.
Format:
Books
Series:
For dummies
--For dummies
General Note:
Includes index.
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.
Abstract:
"Jobs in data science abound, but few people have the data science skills needed to fill these increasingly important roles in organizations. Data Science For Dummies is the perfect starting point for IT professionals and students interested in making sense of their organization's massive data sets and applying their findings to real-world business scenarios. From uncovering rich data sources to managing large amounts of data within hardware and software limitations, ensuring consistency in reporting, merging various data sources, and beyond, you'll develop the know-how you need to effectively interpret data and tell a story that can be understood by anyone in your organization." -- Publisher's description.
Added Author:
