The quality of that dataset is directly related to the organization that manufactures it and how that organization works on data quality.
The sustainability of our model could also be related to the quality of data in the organization.
Beyond data engineering, the accuracy of the model itself, and the performance in its production, if the organization it serves does not have data quality as a priority, probably the model will not be sustained over time.
We apply three different techniques of hyperparameter optimization on a classification model set to compare their accuracy.
Try an image classification model with an unbalanced dataset, and improve its accuracy through data augmentation techniques. Link to the full text in
We present our case of success in classifying user tickets by applying different techniques on natural language processing. With our model, we can determine the