artificial neural networks

Convolutional Neural Networks (CNN)

Convolutional Neural Network (CNN) is an neural network which extracts or identifies a feature in a particular image and is the basis of GoogleNet and VGG19 and used for object detection and classification. CNN has five basic components Convolution, ReLU, Pooling, Flattening and Full connection.

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Feed Forward Neural Networks

A feedforward neural network is an Artificial Neural Network in which connections between the nodes do not form a cycle. Learn about how it uses ReLU and other activation functions, perceptrons, early stopping, overfitting, and others. See the architecture of various Feed Forward Neural Networks

machine learning

Types of Neural Network optimizations

The types of neural network optimizations are weight pruning, structured pruning, convolution, fully-connected, structured group, structure ranking with activations like Lp norm, block pruning, model thinning, compression schedule, regularization, group lasso, group variance, quantization and others

machine learning

Artificial Neural Networks

An Artificial Neural Network is a form of computing system that vaguely resembles the biological nervous system. It is composed of very many neurons that are centres of computation and learn by a sort of hit and trial method over the course of many epochs. ANN can be seen as a network of perceptrons