AI360

Course Name: 

Pattern Recognition (AI360)

Programme: 

B.Tech (AI)

Category: 

Programme Specific Electives (PSE)

Credits (L-T-P): 

(3-0-2) 4

Content: 

Introduction to Model Selection, Decision Theory, Information Theory; Linear Models for Regression and Classification, Neural Networks: Network Training, Jacobian/Hessian Matrices, Regularization, Mixture Density Networks, Bayesian Networks; Computational Learning Theory, Kernel Methods, Sparse Kernel Machines, Graphical Models, Markov Random Fields, Expectation Maximization, Approximate Inference, Factorized Distributions, Expectation Propagation, Hidden Markov Models, Linear Dynamical Systems, Hybrid Model Construction- Boosting, Tree-based models, Conditional Mixture Models, Q-learning and Policy Gradient, PR Applications.

References: 

Pattern Recognition and Machine Learning, Christopher Bishop, Springer, 2006.
Pattern Classification, Duda, Hart, and Strok, Wiley, latest edition.
Pattern recognition, Theodoridis, Sergios, Koutroumbas, Konstantinos, Elsevier.
Introduction to Neural Networks, Heaton, Jeff, Heaton research, 2nd edition, 2008
Pattern Recognition - Narasimha Murthy and Susheela Devi (Univeristies Press, 2011)

Department: 

Information Technology
 

Contact us

Head of the Department,
Department of Information Technology,
National Institute of Technology Karnataka,
SurathkalP. O. Srinivasnagar, Mangalore - 575 025
Ph.:    +91-824-2474056
Email:  hodit [at] nitk [dot] edu [dot] in
 

Web Admin: Sowmya Kamath S

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