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Imperial Library
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Index
Cover
Introduction
What Am I Doing Here?
A Workable Definition of Data Science
But Wait, What about Big Data?
Who Am I?
Who Are You?
No Regrets. Spreadsheets Forever
Conventions
Let's Get Going
Chapter 1: Everything You Ever Needed to Know about Spreadsheets but Were Too Afraid to Ask
Some Sample Data
Moving Quickly with the Control Button
Copying Formulas and Data Quickly
Formatting Cells
Paste Special Values
Inserting Charts
Locating the Find and Replace Menus
Formulas for Locating and Pulling Values
Using VLOOKUP to Merge Data
Filtering and Sorting
Using PivotTables
Using Array Formulas
Solving Stuff with Solver
OpenSolver: I Wish We Didn't Need This, but We Do
Wrapping Up
Chapter 2: Cluster Analysis Part I: Using K-Means to Segment Your Customer Base
Girls Dance with Girls, Boys Scratch their Elbows
Getting Real: K-Means Clustering Subscribers in E-mail Marketing
K-Medians Clustering and Asymmetric Distance Measurements
Wrapping Up
Chapter 3: Naïve Bayes and the Incredible Lightness of Being an Idiot
When You Name a Product Mandrill, You're Going to Get Some Signal and Some Noise
The World's Fastest Intro to Probability Theory
Using Bayes Rule to Create an AI Model
Let's Get This Excel Party Started
Wrapping Up
Chapter 4: Optimization Modeling: Because That “Fresh Squeezed” Orange Juice Ain't Gonna Blend Itself
Why Should Data Scientists Know Optimization?
Starting with a Simple Trade-Off
Fresh from the Grove to Your Glass…with a Pit Stop through a Blending Model
Modeling Risk
Wrapping Up
Chapter 5: Cluster Analysis Part II: Network Graphs and Community Detection
What Is a Network Graph?
Visualizing a Simple Graph
Brief Introduction to Gephi
Building a Graph from the Wholesale Wine Data
How Much Is an Edge Worth? Points and Penalties in Graph Modularity
Let's Get Clustering!
There and Back Again: A Gephi Tale
Wrapping Up
Chapter 6: The Granddaddy of Supervised Artificial Intelligence—Regression
Wait, What? You're Pregnant?
Don't Kid Yourself
Predicting Pregnant Customers at RetailMart Using Linear Regression
Predicting Pregnant Customers at RetailMart Using Logistic Regression
For More Information
Wrapping Up
Chapter 7: Ensemble Models: A Whole Lot of Bad Pizza
Using the Data from Chapter 6
Bagging: Randomize, Train, Repeat
Boosting: If You Get It Wrong, Just Boost and Try Again
Wrapping Up
Chapter 8: Forecasting: Breathe Easy, You Can't Win
The Sword Trade Is Hopping
Getting Acquainted with Time Series Data
Starting Slow with Simple Exponential Smoothing
You Might Have a Trend
Holt's Trend-Corrected Exponential Smoothing
Multiplicative Holt-Winters Exponential Smoothing
Wrapping Up
Chapter 9: Outlier Detection: Just Because They're Odd Doesn't Mean They're Unimportant
Outliers Are (Bad?) People, Too
The Fascinating Case of Hadlum v. Hadlum
Terrible at Nothing, Bad at Everything
Wrapping Up
Chapter 10: Moving From Spreadsheets into R
Getting Up and Running with R
Doing Some Actual Data Science
Wrapping Up
Conclusion
Where Am I? What Just Happened?
Before You Go-Go
Get Creative and Keep in Touch!
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