Foundations of Machine Learning Algorithms (MA722)

Course Name: 

Foundations of Machine Learning Algorithms


M.Tech (CDS)




Programme Core (PC)

Credits (L-T-P): 

(3-0-2) 4


Foundations of Linear Algebra and Matrix Theory, Introduction to Learning, Different learning models: Supervised,
Unsupervised, reinforcement etc., Dimensionality reduction (Linear): PCA, LDA etc. Bayesian Learning: QDA, LDA,
Bayesian belief network, Decision tree learning, Conceptual Learning, Artificial Neural Nets, Classification, regression
and clustering: SVM, Kernel SVM, Linear and Logistic regression, KNN, K-Means. Reinforcement learning


EthemAlpaydin, “Introduction to machine learning”, second edition, PHI publication, 2010. Tom Mitchell, “Machine Learning”, McGraw Hill, 1997 Christopher M. Bishop, “Pattern Recognition and Machine Learning”, Springer, 2006.


Mathematical and Computational Sciences

Contact us

Dr. P. Sam Johnson, Professor and Head
Department of MACS, NITK, Surathkal
P. O. Srinivasnagar, Mangalore - 575 025
Karnataka, India.

  • Hot line: +91-0824-2474048

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