CNNALGORITHM

1. 1. LSTM is suitable for

• sequence prediction tasks and excels in capturing long-term dependencies

• only sequence prediction tasks

• excels in capturing long-term dependencies

• none

2. What is the primary purpose of a Recurrent Neural Network (RNN)?

• Image classification

• Text generation

• Reinforcement learning

• Object detection

3. 3.What is the purpose of the bidirectional RNN architecture?

• a)To handle sequential data in both forward and backward directions

• b) To reduce the computational complexity of the network

• c) To adjust the learning rate during training

• d) None of the above

CNN is most useful when there is an

• a. structured data

• b. unstructured data

• both a and b

• none

which of the following are limitations of deep learning

• a. Data Labeling

• b. Obtain Huge Training Datasets

• 
  Both a and b

• none of the above

6. 6. What is the purpose of the recurrent connection in an RNN?

• a) To propagate the hidden state across different time steps

• b) To adjust the weights and biases of the network

• c) To reduce the dimensionality of the input data

• d) None of the above

5. 7. When is it appropriate to use a Long Short-Term Memory (LSTM) network?

• For tasks requiring only short-term memory

• For tasks requiring long-term memory and capturing dependencies over long sequences

• For tasks requiring real-time processing only

• None of the above

8. 8. What is the main advantage of using Convolutional Neural Networks (CNN)?

• Efficient feature extraction from structured data

• Efficient feature extraction from unstructured data

• Both a and b

• None of the above