Book description
Discover how data science can help you gain in-depth insight into your business - the easy way!
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.
Provides a background in data science fundamentals before moving on to working with relational databases and unstructured data and preparing your data for analysis
Details different data visualization techniques that can be used to showcase and summarize your data
Explains both supervised and unsupervised machine learning, including regression, model validation, and clustering techniques
Includes coverage of big data processing tools like MapReduce, Hadoop, Dremel, Storm, and Spark
It's a big, big data world out there - let Data Science For Dummies help you harness its power and gain a competitive edge for your organization.
Table of contents
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- Cover
- Foreword
- Introduction
- Part I: Getting Started With Data Science
-
Part II: Using Data Science to Extract Meaning from Your Data
- Chapter 4: Introducing Probability and Statistics
- Chapter 5: Clustering and Classification
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Chapter 6: Clustering and Classification with Nearest Neighbor Algorithms
- Making Sense of Data with Nearest Neighbor Analysis
- Seeing the Importance of Clustering and Classification
- Classifying Data with Average Nearest Neighbor Algorithms
- Classifying with K-Nearest Neighbor Algorithms
- Using Nearest Neighbor Distances to Infer Meaning from Point Patterns
- Solving Real-World Problems with Nearest Neighbor Algorithms
- Chapter 7: Mathematical Modeling in Data Science
- Chapter 8: Modeling Spatial Data with Statistics
- Part III: Creating Data Visualizations that Clearly Communicate Meaning
- Part IV: Computing for Data Science
- Part V: Applying Domain Expertise to Solve Real-World Problems Using Data Science
- Part VI: The Part of Tens
- About the Author
- Cheat Sheet
- Advertisement Page
- Connect with Dummies
- End User License Agreement
Product information
- Title: Data Science For Dummies
- Author(s):
- Release date: March 2015
- Publisher(s): For Dummies
- ISBN: 9781118841556
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