29:02

Echelon form and Inverse of a Matrix using Gaussian Elimination

20:40

Decision Tree problem / Finding Best Split using Information Gain

07:45

Issues in Decision tree learning / KTU Machine Learning

11:56

Structure in C programming

19:16

Array access using pointers in C programming

16:35

Storage classes in C - part 2 (Static and Extern)

08:12

Matrix addition in C programming EST102

15:56

Matrix multiplication in C programming EST102

10:25

C Program to count vowels in a String

13:37

Program for Inserting element into array in C

10:59

Program for deleting element from array in C

13:40

Email security in network security

21:09

Decision tree - Entropy and Information gain with Example

17:25

Loops - while loop in C

10:11

for loop in C programming with example

13:15

Internet Key Exchange (IKE) - Phases

22:26

Expectation maximization algorithm / KTU Machine Learning

07:59

Soft Margin Hyperplane or Soft SVM / KTU Machine learning

19:24

Support vector machine (SVM) - part 2 / Mathematical formulation of SVM / KTU Machine learning

20:09

Basics of Support Vector Machine - part 1 / KTU Machine Learning

23:30

Hierarchical Clustering - Problem / Complete linkage / KTU Machine learning

19:55

Hierarchical clustering - Agglomerative and Divisive method/ KTU / Machine learning

18:02

K-means Clustering Example / KTU Machine learning

11:15

K-means Clustering algorithm / KTU Machine learning

13:13

ML estimate of Poisson and Geometric distribution

23:09

Maximum likelihood estimation (MLE) / Parameter estimation of Bernoulli / KTU Machine learning

17:19

Naive bayes or bayesian classifier problem / KTU Machine learning

17:19

Bayesian classifier / Naive bayes algorithm / KTU Machine learning

19:12

Bayes theorem with problems solved / KTU machine learning

10:08

ROC Curve - Example / KTU Machine learning

16:33

ROC Curve and AUC / KTU / Machine learning

14:36

Precision and Recall - Problems / KTU / Machine learning

11:39

Precision and Recall / TP FP TN FN / Confusion matrix / KTU / Machine learning

18:05

Cross validation and re-sampling methods / KTU / Machine Learning

23:59

PCA problem / How to compute principal components / KTU Machine learning

16:22

Principal Component Analysis (PCA) / KTU CS / Machine Learning

29:56

Dimensionality reduction - Subset selection / KTU / Machine learning

18:19

Model selection and Generalisation / KTU CS / Machine learning

07:42

Learning multiple classes / One-vs-One / One-vs-All / KTU CS/ Machine learning

19:11

Probably Approximately Correct Learning (PAC) / KTU / Machine learning

22:34

VC Dimension - Examples / KTU CS / Machine learning

25:42

Vapnik Chervonenkis (VC) dimension / KTU CS / Machine learning