Recurrent neural network|Machine Learning|SNS INSTITUTIONS

#snsinstitutions #snsdesignthinkers #designthinking in this video describes about A Recurrent Neural Network (RNN) is a type of neural network designed to process sequential data, where the order of elements is crucial. Unlike traditional neural networks, RNNs have loops that allow information from previous inputs to be fed back into the network, enabling them to remember past information and make predictions based on context. This makes RNNs particularly well-suited for tasks involving language, speech, and time-series data.
1. Recurrent Neurons
The fundamental processing unit in RNN is a Recurrent Unit. They hold a hidden state that maintains information about previous inputs in a sequence. Recurrent units can "remember" information from prior steps by feeding back their hidden state, allowing them to capture dependencies across time.

RNN Unfolding
RNN unfolding or unrolling is the process of expanding the recurrent structure over time steps. During unfolding each step of the sequence is represented as a separate layer in a series illustrating how information flows across each time step.

Видео Recurrent neural network|Machine Learning|SNS INSTITUTIONS канала S.Saranya SNS