Usage example

In this part,we will illustrate how to perform a classification task using AutoML module.

In this example we will use wine data to predict the type of the wine red or white, through the process we will understand the features of this data, generate automatic static reports and how buiding the model, evaluating it and making predictions, all that can be done in a very short easy way.

1 - Set the experiment parameters and discover your data

After setting the experiment parameters from the side bar , we can go to the development bar to show and describe data.

2 - Generate statistic reports

To generate statistic reports, you have two options sweet and profile, both of them will generate a report that include details and graphs showing the distribution of each features.

Close the side bar for better view, and reopen it when you are done exploring your data.

3 - Building model and Evaluation

When you start building your model , the app will process multiple algorithms to find the best model, this action may take time depending on the size of your data, please be patient while the app is trying to find the best result for you. when the training is completed, then you can evaluate your model.

4 - Predict

If you happy with the accuracy of the model built, you can pass to step 4 and make prediction, either by filling the boxes with appropriate values or drag and drop a file in case of multiple observations. and click predict.

5 - Save your experiment

At the end of the side bar you will find a button, click Save My Experiment and all of your generated output files (images, models, predicted data, statitstic report and logs) will be saved in experiment folder.