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classify sentiments as positive or negative based on customer reviews.predict future product sales volume based on historical sales data.You can bring many different scenarios to Model Builder, to generate a machine learning model for your application.Ī scenario is a description of the type of prediction you want to make using your data. This name is applied to the consumption, training, and model files. When you create your mbconfig file, you're prompted for a name.
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Model.zip: This is a serialized zip file which represents your trained ML.NET model.You can use this pipeline for re-training your model. : This file contains the training pipeline (data transforms, algorithm, algorithm hyperparameters) chosen by Model Builder to train the model.: This file contains the ModelInput and ModelOutput schemas as well as the Predict function generated for consuming the model.The mbconfig file keeps track of everything you do in Model Builder to allow you to reopen the session.Īfter training, three files are generated under the *.mbconfig file: This will create an mbconfig configuration file inside of the project. When you first start up Model Builder it will ask for you to name the project.