Question
In deep learning, which type of neural network is most
suitable for sequential data like time series?Solution
Correct Option: Recurrent Neural Networks (RNNs) (C) are designed for handling sequential data by maintaining a memory of previous inputs, making them ideal for time series and sequence-based problems. Why Other Options Are Wrong: A) CNNs: Convolutional Neural Networks are mainly used for image processing tasks and are not suitable for sequential data. B) FNNs: Feedforward networks do not have memory, making them unsuitable for sequential data where prior inputs are important. D) GANs: GANs are used for generating new data based on learned distributions, not for processing sequences. E) RBFNs: These are used in certain kinds of regression and classification tasks, but they do not excel at handling sequential or time-series data.
Dog : Puppy :: Deer :Â ?
Clock : Time :: Scale : ?
If 38 @ 9 = 66 and 63 @ 43 = 122, then 29 @ 57 = '?'.
Select the option that is related to the third term in the same way as the second term is related to first term and the sixth term is related to the fi...
Select the option that is related to the third number in the same way as the second number is related to the first number.
67 : 96 :: 45 : ?
Select the option that is related to the third number in the same way as the second number is related to the first number.
31 : 90 :: 43 : ?
If BAG = 217 and GATE = 71205, then BAKERY =Â
Select the option that is related to third letter- cluster in the same way as the second – letter cluster is related to the first letter- cluster.
Select the option that is related to the third number in the same way as the second number is related to the first number.
25: 175 :: 38:?
Select the option that is related to the fifth number in the same way as the second number is related to the first number and the fourth number is relat...