deep recurrent neural network
Deep Recurrent Neural Network (DRNN) is like a really smart robot that can "remember" things. It's a type of artificial intelligence (AI) that can learn how to do things. For example, if you gave it a lot of images of cars, it could eventually learn to recognize and label different types of cars.
DRNNs use a special type of neuron called a “recurrent neuron” which is connected to other neurons in a loop. The way these neurons work is that each time the DRNN processes a new input (like a new image of a car), it remembers some information from the last input and uses that information to help it understand the new input.
DRNNs are used in many different areas, like speech recognition and natural language processing, as well as many other applications. They are good at understanding patterns and making predictions based on past data.
DRNNs use a special type of neuron called a “recurrent neuron” which is connected to other neurons in a loop. The way these neurons work is that each time the DRNN processes a new input (like a new image of a car), it remembers some information from the last input and uses that information to help it understand the new input.
DRNNs are used in many different areas, like speech recognition and natural language processing, as well as many other applications. They are good at understanding patterns and making predictions based on past data.