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DATA SCIENCE: THE MAIN COURSE
I Can Science Data, and So Can You!
Arthur Doler
@arthurdoler
arthurdoler@gmail.com
TITANIUM SPONSORS
Platinum Sponsors
Gold Sponsors
HOW MANY APPETIZERS HAVE YOU EATEN?
Sources: Mediawiki, Publicdomainpictures.net
SO WE’RE SKIPPING RIGHT TO THE MAIN
COURSE
YOU HAVE THE DATA
YOU HAVE THE POWER
Sources: Mattel, he-manreviewed.net
WHAT’S FOR DINNER
Picking your problem
Using Knitr/R Markdown
Building a linear predictor
Making a predictive, repeatable
document
WHAT’S NOT FOR DINNER
Learning R
Exhaustive discussion of statistics
Exhaustive discussion of regression
modeling
Ways to run R in production
STEP 0: KNOW YOUR RECIPE FOR
REPEATABILITY
Learn to Knit you some R
knitr ≈ Sweave + cacheSweave + pgfSweave + weaver +
animation::saveLatex + R2HTML::RweaveHTML +
highlight::HighlightWeaveLatex + 0.2 * brew + 0.1 *
SweaveListingUtils + more
Source: Reddit
R Code
Markup
R Code
Markup
Markup
WHAT?! WHY IS THIS A GOOD IDEA?
Do you love
me?
Y
N
LET’S GO FIND THAT RECIPE!
Source: Reddit
STEP 1: SHOP FOR YOUR INGREDIENTS
Finding the question to ask
WHAT ARE YOU TRYING TO DO?
Finding or proving a correlation
Looking for outliers
Building a predictive model
LET’S BUILD A LINEAR PREDICTIVE MODEL
Source: Wikipedia
WHAT ARE YOUR VARIABLES?
• Material Category
• Material ID
• Time-to-Incapacitation
• 1000 / Time-To-Incapacitation
• Carbon Monoxide
• Hydrogen Cyanide
• Hydrogen Sulfide
• Hydrochloric Acid
• Hydrobromic Acid
• Nitrogen Dioxide
• Sulfur Dioxide
WHAT DO YOU CARE ABOUT?
FORMULATE YOUR QUESTION
LET’S HEAD TO THE STORE!
Source: Reddit
STEP 2: GET YOUR MISE EN PLACE
Dividing your data
WHERE IS THE VALUE IN A PREDICTIVE MODEL?
WE BUILD OUR MODEL WITH A TRAINING SET
PARTITIONING YOUR DATA PREVENTS
OVERTRAINING
²⁄³ Training
¹⁄³ Test
½ Training
¼ Test
¼
Validation
LET’S MEASURE EVERYTHING OUT!
Source: Reddit
STEP 3: COOK UP YOUR PREDICTOR
Training your model
ONE WARNING FIRST
DO YOU NEED TO UNDERSTAND YOUR
PREDICTOR?
LET’S GO COOK UP THE MODEL!
Source: Reddit
WHY DID 1000/TIME_TO_INCAPACITATION
WORK BETTER?
STEP 3A: TRIM THE FAT
Eliminating Outliers
LET’S GO CUT!
Source: Reddit
STEP 4: GARNISH WITH GRAPHICS
Adding visualizations to your report
plot ggplot2
Source: Wikimedia
LET’S FINISH UP THAT REPORT!
Source: Reddit
1. Know Your Recipe for Repeatability
2. Shop for Your Column Ingredients
3. Get your Data Divided
4. Cook Up Your Predictor
1. Trim the Outlier Fat
5. Garnish with Graphics
QUESTIONS?
Source: Reddit

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Data Science: The Main Course @ KCDC 2016