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Data identification algorithms are useful models in areas of research and technological development where pattern recognition functions are required to classify data within a definition; the domain symmetry model is a highly efficient Machine Learning algorithm for data identification, capable of classifying images and sounds with a low amount of training data, besides being a model capable of extrapolating to the identification of other types of data thanks to its modeling stage where a contextualization on the nature of the data is applied for the training of the system.Throughout this book the automation of this model is developed and implemented; a model of accessible implementation, with a low computational cost, since it requires a very low amount of training data, fast, versatile in multiple applications and highly efficient.