BASIC LEARNING PRINCIPLES OF ARTIFICIAL NEURAL NETWORKS - Karimova, Mavzuna (Educational Research in Universal Sciences, 2023)
Neural networks have many important properties, but the main one is the ability to learn. Training a neural network is primarily about changing the strength of synaptic connections between neurons. The following example clearly shows this. In Pavlov’s classic experiment, a bell was rung before each dog was fed. The dog quickly learned to associate the ringing of the bell with food. This was due to increased synaptic connections between the parts of the brain responsible for hearing and the salivary glan A difficult and time-consuming part of the process of developing a neural network is training it. A neural network is required to "work" on tens of millions of input data sets in order for it to be able to correctly solve the given tasks. Andrey Kalinin and Grigory Bakunov associate the spread of neural networks with the emergence of various accelerated learning technologies.