/Pattern-Recognition-and-Machine-Learning-PRML-

M.Tech 2nd Semester

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Pattern Recognition and Machine Learning (PRML) [Subject Code - IT-542]

M.Tech 2nd Semester

Course Subject

In This Subject following topics were covered : -

  • Multi Variate Normal Distribution.
  • Maximum Likelihood Estimation.
  • Bayesian Classifier.
  • Bayes decision rule under normality assumption.
  • Parameter Estimation.
  • KNN desnity estimation procedure.
  • Naive Bayes Classifier.
  • Unsupevised Classification.
  • Minimum within cluster distance.
  • K Means Algorithm.
  • Fuzzy K Means Algorithm.
  • Kernal Density Estimation.
  • Principle Component Analysis.
  • Non Linear Dimensionality Reduction.
  • Regression
  • Logistic Regression
  • Gaussian Mixture Model
  • Expectation Maximization Algorithm (EM Algorithm)
  • Support Vector Machines

Note: Above mentioned topics are not in the order in which they were covered