DL TAZAA KHABAR 💥💥
1.Explain Gradient Descent in Deep Learning.
2. Explain the dropout method and it's advantages.
3.What are the Three Classes of Deep Learning, explain each?
4. Explain and analyze the architectural of AlexNet and LeNet Convolution Neural Network.
5.What are the different types of Gradient Descent methods, explain any three of them.
6.Comment on the significance of Loss functions and explain different types of Loss functions while training a network.
7. Explain any three types of Autoencoders.
8.What is the significance of Activation Functions in Neural Networks, explain different types Activation functions used in NN.
9. Explain Generative Adversarial Networks Architecture and its applications.
10.What are Feed Forward Neural Network?
11.Explain the architecture of CNN with the help of a a diagram.
12.What are the Three Classes of Deep Learning explain each?
13.Explain Regularization Methods.
14.Explain LSTM Model , how it overcome the limitation of RNN.
15.Describe sequence learning problem.
16.Explain Gated Recurrent Unit in detail.
17.Explain RNN architecture in detail.
18.Explain Multilayer perceptron.
