• Attempt any five questions.
• All questions carry equal marks.
Explain Multilayer perception with neat diagram.
Discuss about feed forward neural networks with suitable diagram.
Explain Gradient Descent method in deep learning.
Give a brief discussion on regularization in auto encoders.
Explain the architecture of convolution neural networks with neat diagram.
Define Stochastic pooling. Explain it with example.
Draw the architecture of Deep Recurrent Neural Networks explain in detail.
Explain about Directed graphical methods.
Explain Restricted Boltzmann Machines with example.
Define Deep learning. Give different applications of deep learning.
Explain how decomposition can be done in PCA and SVD.
Explain about Nesterov Accelerated GD.
Explain Back propagation through time with examples.
Explain speech recognition techniques in detail.
Image recognition
Video analytics
Weight decay
