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Build AI models on past data with one-click using Automated Machine Learning (AutoML) and then make predictions on unseen data. If you are a data scientist, or working with one, export to Jupyter code and share your experimentation details in a central database (MLflow). Your team will save significant amount of time by avoiding to start coding from scratch and by collaborating better

Create a Model

You need to have a Cloud Worker ready for the model creation process and start the model creation process with our data on the Cloud Worker.


We create a model of regression type by selecting the target column revenue using the ice cream data. You can also limit the model with the advanced options section and select build excel for model.


When the model creation process is finished, some options appear.


You can load the model in Excel, register it in MLflow, see the details of the experiment with MLflow, you can see the code with Jupyter Notebook.