Practical Problem Solving with Data - Onlab Data Conference, Tokyo

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Practical problem solving with data involves more than just visualization or applying the latest machine learning techniques. Intuition, domain knowledge, and reasonable approximations can mean the difference between a successful model and a catastrophic failure. Good problem solvers deeply analyze available data, improvise solutions using their unique assets, anticipate outcomes and issues, and adapt their techniques over time.

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Practical Problem Solving With Data

Pete Skomoroch@peteskomoroch

Onlab Data ConferenceJune 22, 2012

To solve hard problems:

Think like a street fighter

Analyze

Improvise

Anticipate

Adapt

How does this apply to startups?

Analyze

The Men Who Stare at Charts

Look at your data

Averages Suck

0"

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1" 2" 3" 4" 5" 6" 7" 8" 9" 10"

Build a Viewer App

Algorithmic Intuition

Improvise

Extract

Anticipate

Use Your Viewer App

Adapt

Look at your errors

• Sanity check row counts

• Track errors over time

• Find patterns in the error data

• Add missing features to models

• Replace models entirely

Analyze

Improvise

Anticipate

Adapt

Think like a street fighter

Pete Skomoroch@peteskomoroch

Onlab Data ConferenceJune 22, 2012