Neural Networks math Other complex

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Some of them deal with images and recognize them others process sounds and then understand them and some of them process the natural language spoken by humans and then understand them and respond to them as well. for example  Convolutional Neural Networks CNN or Convolution Neural Network specialize in pattern recognition and are widely used in image processing including image recognition and face recognition.

Recurrent Neural Networks  RNN or Recurrent Neural Networks They specialize in understanding sequences and dealing with them of different types. Therefore they are used in many fields such as mac Belgium WhatsApp Number Data hine translation processing the human genetic code and many other fields. There are dozens or even hundreds of other neural networks that work as algorithms in order to perform many human characteristics such as seeing listening speaking understanding…. and so on. A normal neural network works through a mathematical model based on layers and on neural units that produce mathematical values ​​and numbers that determine the outputs of these networks.





They are similar to regular neurons in that they require some amount of energy or electrical charges to be activated. This is exactly what is done through neural networks and their layers as electricity in human nerves is simulated with mathematical values. networks work this way too but with a large number of layers probabilities values ​​and functions. A network such as a convolutional neural network CNN works through a large successive number of hidden layers which work to identify and recognize visual patterns. In the end you can fully recognize images... even if they are as accurate as a human face or eye.