Set up AutoML teradataml Widgets | teradatamlwidgets - Set up AutoML teradataml Widgets

Create a notebook (i.e., Jupyter notebook, Google collab, etc). There is an existing notebook in the demos folder – "AutoML Tutorial.ipynb". The following steps use the Jupyter notebook. See auto_ml.Ui.

Import teradatamlwidgets for auto_ml.
```
from teradatamlwidgets import auto_ml
```
Call the teradatamlwidgets using Ui constructor.
```
ui = auto_ml.Ui(training_table=iris_train)
```

Optional Arguments

Use the optional arguments to set up parameters in the constructor itself. When you run the cell, the UI gets populated with the pre-selected choices. Each parameter has an argument associated which is what would be used to set it in the constructor.
You can see the argument for a given parameter by hovering over the parameter, this will give description of the parameter and at the end specifies the argument name.

This allows the UI to have that selection upon loading (i.e., when the notebook cell is run).
```
from teradatamlwidgets import auto_ml
```
```
ui = auto_ml.Ui(
   task="Classification"
   training_table=iris train
   predict_table='iris_input'
   algorithms=['xgboost', 'knn'],
   verbose=0,
   max_runtime_secs=300,
   max_models=5
)
```

Set up AutoML teradataml Widgets | teradatamlwidgets - Set up AutoML teradataml Widgets - Teradata VantageCloud Lake

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