AutoML enables developers to train high-quality models specific to their business needs.
I used AutoML to build and use the diabetes binary classification model I described here.
I created a new dataset
I uploaded the csv file (minimum size is 1000 rows)
The data was imported
AutoML detected 9 columns
I selected "Outcome" as the Target column
I trained the AutoML model
I specified a budget of one hour
Training started
Training progressed
Training completed
I reviewed the Confusion matrix (the true positives. false positives, true negatives and false negatives)
I reviewed the Feature importance summary
I deployed the model to the cloud
I clicked the DEPLOY button
The deployment completed
I entered test data and asked the model to predict the "Outcome" value
