Nodes
In data science, nodes refer to the individual units that make up a neural network. These nodes are connected to each other through pathways that allow for the transmission of data between them. Each node receives input data, processes it using a mathematical function, and then passes the output to the next node in the network. Nodes can be organized into layers, with each layer performing a specific type of processing. The input layer receives the initial data, while the output layer produces the final result. Hidden layers, located between the input and output layers, perform intermediate processing steps. Nodes can also have weights and biases associated with them, which are adjusted during the training process to optimize the network's performance.
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