by Michele Laurelli
A computational model inspired by biological neural networks, consisting of interconnected nodes (neurons) that process information.
A neural network is a machine learning model inspired by the human brain's structure. It consists of layers of interconnected nodes (neurons) that process and transform input data to produce output predictions.
Neural networks typically have:
Networks learn through backpropagation, adjusting weights to minimize error between predictions and actual outputs.
Image classification
Speech recognition
Natural language processing
A subset of machine learning using neural networks with multiple layers to learn hierarchical representations of data.
An algorithm for training neural networks by calculating gradients of the loss function with respect to weights.
A mathematical function applied to a neuron's output to introduce non-linearity into the network.