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Data Science For Dummies® To view this book's Cheat Sheet, simply go to www.dummies.com and search for “Data Science For Dummies Cheat Sheet” in the Search box. Table of Contents
Оглавление1 Cover
4 Introduction About This Book Foolish Assumptions Icons Used in This Book Beyond the Book Where to Go from Here
5 Part 1: Getting Started with Data Science Chapter 1: Wrapping Your Head Around Data Science Seeing Who Can Make Use of Data Science Inspecting the Pieces of the Data Science Puzzle Exploring Career Alternatives That Involve Data Science Chapter 2: Tapping into Critical Aspects of Data Engineering Defining Big Data and the Three Vs Identifying Important Data Sources Grasping the Differences among Data Approaches Storing and Processing Data for Data Science
6 Part 2: Using Data Science to Extract Meaning from Your Data Chapter 3: Machine Learning Means … Using a Machine to Learn from Data Defining Machine Learning and Its Processes Considering Learning Styles Seeing What You Can Do Chapter 4: Math, Probability, and Statistical Modeling Exploring Probability and Inferential Statistics Quantifying Correlation Reducing Data Dimensionality with Linear Algebra Modeling Decisions with Multiple Criteria Decision-Making Introducing Regression Methods Detecting Outliers Introducing Time Series Analysis Chapter 5: Grouping Your Way into Accurate Predictions Starting with Clustering Basics Identifying Clusters in Your Data Categorizing Data with Decision Tree and Random Forest Algorithms Drawing a Line between Clustering and Classification Making Sense of Data with Nearest Neighbor Analysis Classifying Data with Average Nearest Neighbor Algorithms Classifying with K-Nearest Neighbor Algorithms Solving Real-World Problems with Nearest Neighbor Algorithms Chapter 6: Coding Up Data Insights and Decision Engines Seeing Where Python and R Fit into Your Data Science Strategy Using Python for Data Science Using Open Source R for Data Science Chapter 7: Generating Insights with Software Applications Choosing the Best Tools for Your Data Science Strategy Getting a Handle on SQL and Relational Databases Investing Some Effort into Database Design Narrowing the Focus with SQL Functions Making Life Easier with Excel Chapter 8: Telling Powerful Stories with Data Data Visualizations: The Big Three Designing to Meet the Needs of Your Target Audience Picking the Most Appropriate Design Style Selecting the Appropriate Data Graphic Type Testing Data Graphics Adding Context
7 Part 3: Taking Stock of Your Data Science Capabilities Chapter 9: Developing Your Business Acumen Bridging the Business Gap Traversing the Business Landscape Surveying Use Cases and Case Studies Chapter 10: Improving Operations Establishing Essential Context for Operational Improvements Use Cases Exploring Ways That Data Science Is Used to Improve Operations Chapter 11: Making Marketing Improvements Exploring Popular Use Cases for Data Science in Marketing Turning Web Analytics into Dollars and Sense Building Data Products That Increase Sales-and-Marketing ROI Increasing Profit Margins with Marketing Mix Modeling Chapter 12: Enabling Improved Decision-Making Improving Decision-Making Barking Up the Business Intelligence Tree Using Data Analytics to Support Decision-Making Increasing Profit Margins with Data Science Chapter 13: Decreasing Lending Risk and Fighting Financial Crimes Decreasing Lending Risk with Clustering and Classification Preventing Fraud Via Natural Language Processing (NLP) Chapter 14: Monetizing Data and Data Science Expertise Setting the Tone for Data Monetization Monetizing Data Science Skills as a Service Selling Data Products Direct Monetization of Data Resources Pricing Out Data Privacy
8 Part 4: Assessing Your Data Science Options Chapter 15: Gathering Important Information about Your Company Unifying Your Data Science Team Under a Single Business Vision Framing Data Science around the Company’s Vision, Mission, and Values Taking Stock of Data Technologies Inventorying Your Company’s Data Resources People-Mapping Avoiding Classic Data Science Project Pitfalls Tuning In to Your Company’s Data Ethos Making Information-Gathering Efficient Chapter 16: Narrowing In on the Optimal Data Science Use Case Reviewing the Documentation Selecting Your Quick-Win Data Science Use Cases Picking between Plug-and-Play Assessments Chapter 17: Planning for Future Data Science Project Success Preparing an Implementation Plan Supporting Your Data Science Project Plan Executing On Your Data Science Project Plan Chapter 18: Blazing a Path to Data Science Career Success Navigating the Data Science Career Matrix Landing Your Data Scientist Dream Job Leading with Data Science Starting Up in Data Science
9 Part 5: The Part of Tens Chapter 19: Ten Phenomenal Resources for Open Data Digging Through data.gov Checking Out Canada Open Data Diving into data.gov.uk Checking Out US Census Bureau Data Accessing NASA Data Wrangling World Bank Data Getting to Know Knoema Data Queuing Up with Quandl Data Exploring Exversion Data Mapping OpenStreetMap Spatial Data Chapter 20: Ten Free or Low-Cost Data Science Tools and Applications Scraping, Collecting, and Handling Data Tools Data-Exploration Tools Designing Data Visualizations Communicating with Infographics
10 Index
