Machine Learning

Machine Learning, May - August, 2021

Note: This course will be taken by two instructors. Find the details below.

Find the syllabus by visiting the link. [ Download ]

R1. S. Theodoridis and K. Koutroumbas, Pattern Recognition, 4th edition, Academic Press, 2009.
R2. C. M. Bishop, Pattern Recognition and Machine Learning, Springer, 2006.
R3. S. Haykin, Neural Networks-A Comprehensive Foundation, Pearson Education, 2001.
R4. T. M. Mitchell, Machine Learning, McGraw Hill,1997.
R5. T. Hastie, R. Tibshirani, and J. Friedman, The Elements of Statistical Learning, 2nd Edition, Springer, 2009.
R6. E. Alpaydin, Introduction to Machine Learning, MIT, 2004 ( PHI-2006 ).
R7. A. Géron, Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow, 2nd Edition, O’Reilly Media, 2019

Note: This evaluation pattern may subject to change due to COVID-19 pandemic.

[ Not a updated list ]

Class No	Date	Time	Duration	ReadingList / Resources	Contents Discussed
1	-	-	1.0 hr	-	Introduction to Machine Learning and Motivation
2	-	-	1.0 hr	[ Slides ]	The machine learning landscape
3	25/05/21	11:10	1.0 hr	Class Lecture	Bayesian Classifier for 2 class problem and Average Error
4	31/05/21	11:10	1.0 hr	Lect 03_04 [ Class note ]	Generalised Bayes theory, minimum risk classifier, minimum error-rate classifier
5	03/06/21	12:15	1.0 hr	Class Lecture	Classifier, discriminant function, Gaussian distribution for univariate and multivariate case
6	07/06/21	11:10	1.0 hr	Class Lecture [ Class note ]	Variance-covariance matrix: physical interpretation, example, detailed description of multivariate normal distribution
7	09/06/21	12:15	1.0 hr	Class Lecture [ Class note ]	Bivariate normal density: mathematical desription, physical interpretation
8	14/06/21	11:10	1.0 hr	Class Lecture [ Class note ]	Case 1: Discriminant funtion for normal density (detailed mathematical derivaiton and physical interpretation)
9	15/06/21	11:10	1.0 hr	Class Lecture [ Class note ]	Case 2 and Case 3: Discriminant funtion for normal density (detailed mathematical derivaiton and physical interpretation), Example of Case 2