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Multineural network
Back propagation algo and derivation
.Bayes theorem and probs
.Brute force derivation and problems
.Max likelihood least square error hypothesis derivation
.Max likelihood hypothesis for predicting probabilities derivation
Gradient derivation with and without bp
.Gradient search to max likelihood derivation
Minimum description length principle derivation
Naive bayes classifier 2 probs( with and without using m estimates)
Bayesian belief network diagram and exp
K means derivation
Multinn bp algo
Derivation hidden and op
.Bayes theorem
.Brute force deri
Probs
.Max likehood derivation
Gradient derivation
Min decs princi
.Hmap der
Bayes optimal class no prob
Gibbs algo n hows its diff
Naive bayes class
Probs m esti and without
No continuous
Bayes and belief network diag and exp
K means deri
NO gradient beleief
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