Course Name: 

Deep Learning (IT702)


M.Tech (IT)



Credits (L-T-P): 

(3-0-2) 4


Basics of Applied Math and Machine Learning: Linear Algebra for Machine Learning, Probability and Information Theory, Numerical Computation, Machine Learning Basics.
Deep Networks: Deep Feed Forward Networks, Regularization for Deep Learning, Optimization for Training Deep Models, Convolutional Neural Networks, Sequence Modeling - Recurrent and Recursive Nets. Practical Methodology, Applications of Deep Learning, Deep Generative Models,Research Trends


Josh Patterson and Adam Gibson, "Deep learning: A Practitioner's Approach", O'Reilly, 2017
Ian Goodfellow, Y. Bengio and A. Courville, "Deep Learning", MIT Press, 2016.
Michael A. Nielsen, "Neural Networks and Deep Learning", Determination Press, 2015
Li Deng and Dong Yu, "Deep Learning: Methods and Applications", 2013
Koller, D. and Friedman, N. Probabilistic Graphical Models . MIT Press. 2009

Contact us

Biju R Mohan

Head of the Department,
Department of Information Technology, NITK, Surathkal,
P. O. Srinivasnagar, Mangalore - 575 025
Karnataka, India.
Ph.:    +91-824-2474056
Email:  infotech[AT]nitk[DOT]ac[DOT]in

Sowmya Kamath S (Web Admin)

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