Providing information
During training, a neural network is provided with a training sample and reference correct answers. The sample consists of data on which predictions must be made. It contains a significant amount of data, usually at least ten times more than the number of neurons in the network.
During the training process of a neural network, data is provided not in the form of words, but in the form of mathematical formulas and numerical coefficients. For example, an image of a woman may be assigned the value "1", while an image of a man may be assigned the value "0". This is the simplest example. In practice, real neural networks have a more complex structure and process data using serious mathematical methods.
Transformations
Input neurons receive architect data package information and transform it using mathematical methods before passing the processed information on. This process is similar to how our eyes perceive visual objects and send them to the brain as neural signals. The brain analyzes these signals, which allows a person to understand the world around them. In the context of neural networks, information is analyzed and transformed using mathematical operations, which allows the network to make calculations and decisions based on the input data.
Processing and conclusions
Each neuron in a neural network has an internal parameter called a “weight.” The weight is a numerical value that is determined using special algorithms. The weight of a neuron indicates its importance in the context of the entire network. During the training of a neural network, the weights of neurons are automatically adjusted and tuned.
Training a neural network
As a result of such adjustment, certain neurons can, for example, react to the silhouette of an object and provide information that there is a person in the image. This happens without explicitly describing a person as a set of mathematical figures. Instead, the neural network itself determines the values of the weights that allow it to recognize objects and situations.
Result
The neural network outputs a set of numbers and formulas that are interpreted as probabilities of various outcomes. For example, if it processes the image from the previous example with a man and a woman and the result is 0.67, this can be interpreted as “most likely it is a woman”. However, it is worth remembering how a neural network works. Due to its nature, it is not able to provide an absolutely accurate answer, only a probability. Moreover, due to internal factors and instability of neurons, the results can vary even with the same input data.
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Alexander Kuleshov
Alexander Kuleshov
General Director of Sales Generator LLC
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