Deep Learning

Course Name: 

Deep Learning(CS422/CS422M)

Programme: 

B.Tech (CSE)

Semester: 

Seventh

Category: 

Programme Specific Electives (PSE)

Credits (L-T-P): 

04(3-1-0)

Content: 

linear and non linear activation functions, loss functions, gradient descent method, back propagation algorithm, Deep feed forward networks, Regularization for deep learning, Convolutional neural networks, Optimization for training deep models, RNN, Autoencoders, Popular deep learning architectures published in the last 10 years, Limitations of CNN, Semi-supervised deep learning, Applications (image classification and segmentation).

References: 

Goodfellow, I., Bengio, Y., Courville, A. Deep learning (Vol. 1). Cambridge: MIT press.
Martin T hagan etc, Neural network design (2nd edition), 2014
Taqiq Rashid, Make your own Neural Network, 2016
Tom Mitchell, Machine Learning, McGraw-Hill, 1997
Y. S. Abu-Mostafa et .al , Learning from Data, AMLbook.com

Department: 

Computer Science and Engineering
 

Contact us

Dr. Manu Basavaraju
Head of the Department
Department of CSE, NITK, Surathkal
P. O. Srinivasnagar, Mangalore - 575 025
Karnataka, India.
Hot line: +91-0824-2474053
Email: hodcse[AT]nitk[DOT]ac[DOT]in
            hodcse[AT]nitk[DOT]edu[DOT]in

                      

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