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Module Details

Course : P-15.machine Learning

Subject : Computer Science

No. of Modules : 39

Level : PG

Source : E-PG Pathshala

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Sr. No. Title E-Text Video URL Metadata
1 M-06. probability - Click Here
2 M-10. decision theory and bayesian decision theory - Click Here
3 M-09. information theory - Click Here
4 M-15. classification and regression trees -i - Click Here
5 M-14. decision tree algorithm id3 - Click Here
6 M-13. decision trees - Click Here
7 M-11.classification,nearest neighbours evaluation - - Click Here
8 M-07.probability distributions - - Click Here
9 M-08.linear algebra - - Click Here
10 M-25.cluster analysis and cluster validity - Click Here
11 M-33.expectation and maximization - Click Here
12 M-27.dimensionality reduction - i - Click Here
13 M-28.dimensionality reduction - ii - - Click Here
14 M-30.nave bayes classification - - Click Here
15 M-32.bayesian belief networks-ii - - Click Here
16 M-29.bayes learning - - Click Here
17 M-31. bayesian belief networks- i - - Click Here
18 M-26. semi supervised learning - - Click Here
19 M-01.machine learning introduction - Click Here
20 M-03.design of learning system - Click Here
21 M-04.type of learning-i - Click Here
22 M-05. types of learning-ii - Click Here
23 M-02. internals of machine learning - - Click Here
24 M-18. support vector machines-ii - Click Here
25 M-20.neural networks ii - Click Here
26 M-19. neural networks i - Click Here
27 M-22. genetic algorithms - ii - Click Here
28 M-21.genetic algorithms - i - Click Here
29 M-24.k-means clustering - Click Here
30 M-23.introduction to clustering - Click Here
31 M-16. classification and regression - - Click Here
32 M-17. support vector machines i - - Click Here
33 M-35.hmm baum welsh and viterbi algorithms - Click Here
34 M-38.basics of reinforcement learning - ii - Click Here
35 M-37.basics of reinforcement learning-i - Click Here
36 M-34.markov and hidden markov models - Click Here
37 M-40.temporal difference learning - Click Here
38 M-36.hmm em algorithm - Click Here
39 M-39.q learning - Click Here