An artificial neural network (ANN) is a type of Machine Learning - 20230221102815 model that is inspired by the structure and function of the human brain. It is composed of layers of interconnected "neurons," which are mathematical functions that process and transmit information. These layers are connected by pathways called "edges," which are used to transmit information from one neuron to another.
The input data is fed into the input layer, and it propagates through the network to the output layer, where the final output is produced. The network is trained using a dataset with labeled inputs and outputs. The goal of training is to adjust the parameters of the network (e.g. the weights of the edges) to minimize the error between the output produced by the network and the correct output.
There are different types of ANN, such as feedforward, recurrent, and convolutional neural network. They are used for different applications such as image recognition, natural language processing, speech recognition, or predictive analytics.
Status:: #wiki/notes/germinating
Plantations:: Machine Learning - 20230221102815
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