8. Why I use Domino
• Data science is complicated.
o Knowing how to fit a model is not enough!
o Variety of challenges from data analysis to production.
o There is no one-size-fits-all solution.
• I do not have time/skills for every single task.
• I can use Domino to fill the gaps.
• Focus on understanding problems, improving
models and presenting results.
• Speed up analysis in just a few clicks.
• More time for family and other stuff.
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9. How I use Domino
• Interface
o Web or R
• Examples
o Hello, World! (Iris)
o Stock Market Forecast
• Code Sharing
• Try it Yourself
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14. “Hello, World!” Example
• Classic dataset - Iris
• Four numeric features / predictors (x)
o Sepal Length, Sepal Width, Petal Length and Petal Width
• One categorical target (y)
o Three species of Iris – Setosa, Versicolor and Virginica
• Using R to build a simple predictive model
• Saving the model for future use
• Deploying the model as web service
• Automatic version control
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17. Evaluate and Save
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Print “Random Forest”
model summary
Model with highest
10-fold cross-
validation accuracy
(i.e. best parameter
setting)
Include statistics for
future comparison
Finally, save the model
for future use
19. Deploy
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Point to that script
Specify the function to call
Publish or unpublish the API
Domino automatically keeps all versions of your API
22. Stock Market Forecast
• Historical stock data from Yahoo!
• Using R to generate numeric features (x)
• Target (y) – Next Trading Day % Change in Closing
Price
• Using R to build ensembles for forecast
• Configure scheduled runs
• Automatic version control
• API
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23. Predictive Model
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Historical stock price
data from Yahoo!
x: Multiple Technical Analysis Indicators
y: Next Day % Change in Closing Price
Predictive Model:
Ensemble of xgboost models
For more info, see
app.dominoup.com/jofaichow/example_stock
24. Scheduled Runs
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Point to the R script
Schedule to run at a certain time every
Weekday (more options available)
Re-publish API endpoint so it uses the latest results
Select different hardware tiers
Notify your friends / colleagues / clients
31. Set up your first API
Endpoint in Minutes
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Point it to your own project
Insert your own API key
32. Conclusions
• Data science is complicated.
• Our time is important.
• I can use Domino to save time.
• It helps me to tackle some challenges
that are outside my comfort zone.
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33. Thanks!
• Mango Solutions
• My Colleagues at Domino
• More Info and Feedback
o jofai@dominoup.com
o Twitter: @matlabulous
o http://blog.dominodatalab.com/
• Code
o Iris Example –
https://app.dominoup.com/jofaichow/example_iris
o Stock Example –
https://app.dominoup.com/jofaichow/example_stock
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