Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Sign up for free
Menu
Search
Features
All features
Private URLs
Password Protection
Custom URLS
Scheduled publishing
Remove Branding
Restrict embedding
Deck Collections
Notes
Features
All features
Private URLs
Password Protection
Custom URLS
Scheduled publishing
Remove Branding
Restrict embedding
Deck Collections
Notes
Explore
Featured decks
Featured speakers
Programming
Technology
Storyboards
Explore
Featured decks
Featured speakers
Programming
Technology
Storyboards
Pricing
Search
Sign in
Sign up for free
Insight demo
Search
Kateryna Lapina
February 15, 2016
25
0
Share
Embed
Copy iframe code
Copy JS code
Copy link
Start on current slide
Insight demo
A three-week project completed as part of Insight Data Science
Kateryna Lapina
February 15, 2016
More Decks by Kateryna Lapina
See All by Kateryna Lapina
katerynalapina_demo_final.pdf
lapinak
0
38
Featured
See All Featured
CSS Pre-Processors: Stylus, Less & Sass
bermonpainter
360
31k
Typedesign – Prime Four
hannesfritz
42
3.2k
Odyssey Design
rkendrick25
PRO
2
870
SEOcharity - Dark patterns in SEO and UX: How to avoid them and build a more ethical web
sarafernandez
0
300
Getting science done with accelerated Python computing platforms
jacobtomlinson
2
540
Helping Users Find Their Own Way: Creating Modern Search Experiences
danielanewman
31
3.4k
Skip the Path - Find Your Career Trail
mkilby
1
260
Statistics for Hackers
jakevdp
799
230k
VelocityConf: Rendering Performance Case Studies
addyosmani
331
25k
Code Review Best Practice
trishagee
74
20k
Un-Boring Meetings
codingconduct
0
460
Why Our Code Smells
bkeepers
PRO
340
58k
Transcript
Kateryna Lapina Insight Data Science, Spring 2016 NYCeats: choose your
dining crowd in NYC
New York is famous for its restaurants
New York is famous for its restaurants But which one
suits you best?
New York is famous for its restaurants NYCeats will help
you to choose your dining crowd in NYC & avoid the overrated tourist traps! But which one suits you best?
Data and Algorithm: NYC 800,000 Geo-location User’s home city Local
time Popular with everyone! High Locals! Tourists! Low Local score Tourist score Kernel Density restaurants
Tourists eat here! Example 1: Club A Steakhouse Is this
place touristy? Let’s see if this works
Tourists eat here! Example 1: Club A Steakhouse Is this
place touristy? Let’s see if this works
Locals eat here! Example 2: My Pie Do locals really
go there? Let’s see if this works
Locals eat here! Example 2: My Pie Let’s see if
this works Do locals really go there?
Kateryna Lapina Ph.D., Environmental Engineering Atmospheric Modeling at CU Boulder
Modeling air quality About me
“Locals eat” If local/tourist>1.5 KDE bandwidth 50m Saturday, Sunday “Locals
eat” If local/tourist>1.1 KDE bandwidth 50m Saturday, Sunday “Locals eat” If local/tourist=1.5 KDE bandwidth 100m Saturday, Sunday “Locals eat” If local/tourist=1.5 KDE bandwidth 50m Friday, Saturday, Sunday Sensitivity analysis
Locals eat here! Let’s see if this works Example 3:
Heidi’s House
None