Backpropagation Algorithm – An important mathematical tool for making better and high accuracy predictions in machine learning. This algorithm uses supervised learning methods for training Artificial Neural Networks. The whole idea of training multi-layer perceptrons is to compute the derivatives of the error function or gradient descent with respect […]
“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) – Combination of two neural networks which is a very effective generative model network, works simply opposite to others. The other neural network models take usually complex input and output is simple but in GANs it’s just opposite. GANs are a very young family member of […]
Artificial Neural Networks – As the name suggest “Neural Network”, they are inspired by the human brain system. ANNs were originally designed with biological neurons as a reference point thus sometimes they are called a brain model for computers. It’s more of a framework than an algorithm. ANNs […]