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Chapter 14Figure 15: AutoML Tables: analyzing the results of our training[ 507 ]
An introduction to AutoMLFigure 16: AutoML Tables: deep dive on the results of our trainingNote that manually crafted models available in https://www.kaggle.com/uciml/adult-census-income/kernels get to an accuracy of ~86-90%. Therefore, ourmodel generated with AutoML is definitively a very good result!Figure 17: AutoML Tables: additional deep dive on the results of our trainingIf we are happy with our results, we can then deploy the model in production viathe PREDICT tab (see Figure 18). Then it is possible to make online predictions ofincome by using a REST (https://en.wikipedia.org/wiki/Representational_state_transfer) API, using this command for the example we're looking at in thischapter:[ 508 ]
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An introduction to AutoML
Figure 16: AutoML Tables: deep dive on the results of our training
Note that manually crafted models available in https://www.kaggle.com/uciml/
adult-census-income/kernels get to an accuracy of ~86-90%. Therefore, our
model generated with AutoML is definitively a very good result!
Figure 17: AutoML Tables: additional deep dive on the results of our training
If we are happy with our results, we can then deploy the model in production via
the PREDICT tab (see Figure 18). Then it is possible to make online predictions of
income by using a REST (https://en.wikipedia.org/wiki/Representational_
state_transfer) API, using this command for the example we're looking at in this
chapter:
[ 508 ]
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