Posted On: Nov 26, 2019
The major differences between RNN and CNN are as follows
|1||Full form||The RNN stands for Recurrent Neutral Networks.||The CNN stands for Convolution Neutral Networks.|
|2.||Based upon the suitability||The RNN is best suited for temporal data, also called as the sequential data.||This is best used for processing of images, classification of images and to correlate data.|
|3.||Based on compatibility features||The feature compatibility of RNN is lesser.||The CNN feature compatibility is more.|
|4.||Based on handling input/ output||The RNN is able to handle arbitrary input/output lengths.||The CNN is able to handle only fixed input/output lengths.|
|5.||Based on processing||The RNN is able to use internal memory to process arbitrary sequences of inputs.||CNN is a feed-forward artificial neural network.|
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Tensors can be thought of as vectors and matrices of higher dimensions. They represent n-dimensional arrays of base data-type. Each element of a tensor is of the same data-type which is always known. ...