“Artificial neural networks (ANNs) are biologically inspired computing code with number of simple, highly interconnected processing elements for simulating human brain workings to process information model”.
Conceptually artificial neural networks is inspired by neural networks in the brain but actual implementation in machine learning are way far from reality. Take in multiple inputs, and produce a single output.
Generative Adversarial Networks (GANs) – A very young family member of Deep Neural Networks Architecture. Introduce by Ian Goodfellow and his team at the University of Montreal in 2014. GANs are class of unsupervised machine learning algorithm. Adversarial training “The most interesting idea in the last 10 years in the field […]
Artificial Neural Networks – As the name suggest “Neural Network”, they are inspired by brain system. They were originally designed to about biological neurons (also called as perceptrons). Artificial Neural Networks (ANN) – Some background As per Dr. Robert Hecht-Nielsen, the inventor of one of the first neuron […]
Deep learning is a learning scheme that approaches the learning problem by learning the underlying representations; too much of learning. I thats why its also called as representation learning.