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An introduction to AutoML
At the end, the model is built and it achieves a good precision of 87.6% and recall of
84.1% (see Figure 53):
Figure 53: AutoML Text Classification – precision and recall
If you are interested in playing some more with happiness-related datasets, I suggest
having a look at Kaggle: https://www.kaggle.com/ritresearch/happydb.
Using Cloud AutoML ‒ Translation solution
In this solution, we are going to auto-create a model for translating text from
English to Spanish built on the top of a large model provided by Google as the base.
As usual, the first step is to activate the solution (see Figure 54) and then create a
dataset (see Figure 55):
Figure 54: AutoML Text Translation – accessing the solution
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