Foundations of Machine Learning Algorithms (MA722)
Course Name:
Foundations of Machine Learning Algorithms
Programme:
M.Tech (CDS)
Semester:
First
Category:
Programme Core (PC)
Credits (L-T-P):
(3-0-2) 4
Content:
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
References:
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.
Department:
Mathematical and Computational Sciences
