Implementation
Artificial Neural Networks (ANNs) are a subset of machine learning algorithms that are modeled after the structure and function of the human brain. ANNs consist of layers of interconnected nodes, or neurons, that process and transmit information. Each neuron receives input from other neurons, processes that input, and then sends output to other neurons. ANNs are trained using a process called backpropagation, which adjusts the weights of the connections between neurons to minimize the difference between the predicted output and the actual output. ANNs are used in a variety of applications, including image and speech recognition, natural language processing, and predictive analytics.
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