The foundational structure of the Gated Recurrent Units (GRUs) represents a recurrent neural network (RNN) architecture utilized within the realm of deep learning and also provides an enhanced computational advantage over the Long Short-Term Memory (LSTM), affording it a distinct preference in specific domains.
Deep Learning uses neural networks to create the foundation of the working model architecture. A neural network that took the idea of the human brain working for its basic working model has its basic unit a neuron. Like the human brain artificial neural networks mimic a similar information processing model i.e.:
Deep Learning (DL) employs multiple layers of non-linear training units in order to facilitate feature extraction and transformation. The phenomenon of artificial intelligence has induced significant transformation in contemporary enterprises due to its demonstration of a degree of accuracy in specific endeavors that is akin to human capabilities. A variety of tasks, including but not limited to design acknowledgment, pattern recognition, picture classification, and voice/text interpreting, are frequently employed in the respective field under consideration. Self-driving CAR is one of the best examples and biggest achievements so far.
A technique for implementing machine learning. At the same time I also claim It is absolutely wrong to call Deep Learning as Machine Learning (in my personal opinion). The techniques is to achieve a goal not necessarily come out of same goal. #AILabPage