EC762 Pattern Recognition and Machine Learning

Course Name: 

EC762 Pattern Recognition and Machine Learning






Programme Core (PC)

Credits (L-T-P): 

(4-0-0) 4


Statistical foundations, Different Paradigms of Pattern Recognition, Probability estimation, Proximity measures, Feature extraction, Different approaches to Feature selection, Nearest Neighbor Classifier and variants, Bayes classification. Linear models, regression, logistic regression, neural networks, objective function and learning, back propagation. Kernel based methods, support vector machines. Dimensionality reduction, principal component analysis, reconstruction, discriminant analysis. Clustering, K-means algorithm, distance measure, objective function, initialization. Anomaly detection, recommender systems. Scaling of algorithms.


R. O. Duda, P. E. Hart and D. G. Stork Pattern Classification, Wiley Publications, 2001.
D. McKay, Information Theory, Inference, and Learning Algorithms, Cambridge University Press 2003.
C. M. Bishop, Pattern Recognition and Machine Learning, Springer, 2006.


Electronics and Communication Engineering(ECE)

Contact us

Prof. N. Shekar V. Shet, Proffessor and Head, 
Department of ECE, NITK, Surathkal
P. O. Srinivasnagar,
Mangalore - 575 025 Karnataka, India.

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