Artificial Neural Networks Unveiled
14 June 2023
ANNs are designed after biological neural networks.
They're made up of interconnected nodes or 'neurons'.
ANNs have three types - input, hidden, and output layers.
Weights adjust based on differences between actual and predicted output.
This learning method minimizes error to fine-tune weights.
Deep Learning uses ANNs with multiple hidden layers for complex tasks.
The most basic ANN, it's a single-layer binary classifier.
Activation functions decide if a neuron should be activated.
From image recognition to self-driving cars, the use cases are vast.
They require massive datasets and computational power to function optimally.