Apr 11, 2022
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From the automated treatment of this data and its mobile phone number list algorithms, they can establish predictions and inferences and make decisions. In deep learning , the machine learning process is a little more complex, but both cases are related to algorithms inspired by the structure and function of the brain, and that is why we speak of artificial neural networks ( rna ). the rnathey are computational models that process information by mimicking the functioning of biological neurons, and therefore are composed of nodes or "neurons" that receive, transmit mobile phone number list and send information and are connected as a network. The rna are usually made up mobile phone number list of multiple layers of hidden mobile phone number list nodes, which are the ones that transmit the information between the nodes of the network –input and output–. These layers are known as "learning layers," and the greater the number of layers, the greater the depth of the network mobile phone number list and the greater the ability to learn. These multilayers and their depth give rise to deep learning . It is necessary to highlight from now on that this is a complex mobile phone number list process in which human decisions are also involved, from the design of the data sets for training to the programming of the algorithms themselves, and that they can lead to a biased result. Companies developing such systems argue that to improve efficiency and accuracy and reduce bias, they need to store and analyze more and more data. In the field of health, mobile phone number list these data are personal and sensitive.