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Data preprocessing is where data scientist spent most of their time. These tasks involve selecting the appropriate features as well as clean and prepare them to become the inputs or independent variables in a machine learning model.
Model performance is strictly related with the selection and cleaning of the features. Below we describe common tasks which are necessary to conduct before fitting and evaluate a model. These tasks will improve the accuracy of the model due to the increase of the inputs quality.
