applied data science with yhat
DESCRIPTION
Yhat at the San Francisco Data Science Meetup (02/26/2014)TRANSCRIPT
Applied Data Science with Yhat
SF Data Science Meetup Feb 26, 2014
1) Intro (1 min)2) The Problem (3 mins)3) Case Study: Beer Recommender (5 mins)4) Demo (3 min)5) Q/A (5 min)
Founders Company
InvestorsGreg Lamp, CTO
Austin Ogilvie, CEO ● Launched in 2013● HQ in Brooklyn
Data sciencein the real world.
regression
Get Raw Data
Strategic Insights
Real World Scoring
Data Driven ProductsBusiness Impact
Clean Data
Stages of the Analytics Project Life Cycle
Expert data teams
Management
Customers & Front Line Employees
What makes building analytical apps hard?
Hi, I’m Trey.
Meet Trey, the Data Scientist
We need to reduce churn. Okay. I'll look into it.
I figured out that....some complex stuff about vector space that'll improve...
....and that's how we'll reduce churn.
Sounds good. Let's do that...
Any of you know what Gradient Boosting is?
So when can we go live with the new model?
Now what?
use your tools
use your tools move quickly
use your tools move quickly
any workflow
use your tools move quickly
any workflow no translating
Case Study
+ = ?
A Beer Recommender in Python
The Data
http://snap.stanford.edu/data/web-BeerAdvocate.html
Beers
Users
Ratings
Distance
vs
vs
calculating distance
eeny
? ?
eeny meeny
?
?Cosine
eeny meeny miny
?Cosine
moe
pick one.you can always
change
Thank you,
Scoring
Aggregate
Sort
Filter
Return
Deployment
What does this mean?
Import Yhat
Create a YhatModel
Define execute
Grab incoming data
Call your function
Format and return results
Demohttp://cloud.yhathq.com/http://beers.yhathq.com/
deploy your ownIPython Notebook
Thanks!@yhathq
Questions?