Imagine you're the basketball team's coach, and you want to teach your players how to recognize different strategies used by the opposing teams. To achieve this, you divide your players into smaller groups, with each group responsible for learning a specific aspect of the game, like player movements, passing patterns, or throwing techniques.
A neural network algorithm is similar to this coaching strategy. The neural network is made up of interconnected "neurons" or "nodes" (like the players), organized in layers. Each neuron is responsible for processing a small piece of information or recognizing specific patterns (like the different aspects of the game). The neurons in one layer pass on the information they've processed to the neurons in the next layer, gradually refining and combining the information until the final layer of neurons makes a decision or prediction (similar to identifying the opponent's strategy).
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