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As discussed on our last blog article, Recurrent Neural Networks take as their input not just the current input example they see, but also what they perceived one or more steps back in time. Those previous time steps provide context for the current time step’s data. So RNNs analyse a representation of the current data,… Read More


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A Recurrent Neural Network (RNN) is a class of Artificial Neural Networks, where connections between units form a directed graph along a sequence. The term “recurrent neural network” is used indiscriminately to refer to two broad classes of networks with a similar general structure, where one is finite impulse and the other is infinite impulse.… Read More


Feed Forward

A Feed Forward Neural Net is an artificial Neural Network wherein connections between the nodes always ensure that information always moves in the forward direction and never backwards. Being the first and simplest type of Artificial Neural Network devised in the history of computer science, it is very different from the more advanced neural networks… Read More


Neural Nets Deep Dive_large

As we discussed in our previous blog post, an Artificial Neural Network (ANN), usually called “neural nets” (NNs), is a learning algorithm that is inspired by Biological Neural Networks within our human brains and central nervous-systems. Modern day computations especially those involving Machine Learning for the sake of developing Artificial Intelligence are mostly structured in… Read More


Artificial Neural Networks  In Machine Learning

An Artificial Neural Network (ANN) is a computational algorithmic model. It is based on the structure of biological neural networks within human brains and aim to replicate their functions in order to augment human activities. It ideally aims to work in the way human brains processes information. It includes a large number of connected processing… Read More