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This repository includes 5 of 9 programming assignments solved while taking up Coursera's Probability Graphical Model course.

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Coursera-Probabilistic-Graphical-Models

This repository includes 5 of 9 programming assignments solved while taking up Coursera's Probability Graphical Model course.

Assignments were completed with GNU Octave, version 3.8.0

For more information, refer - https://www.coursera.org/specializations/probabilistic-graphical-models

Course Coverage

  • Bayesian Networks
  • Markov Networks
  • Gibbs Sampling
  • Decision Theory
  • Belief Propogation Algorithms
  • MAP algorithms
  • Makov chain monte carlo sampling
  • Metropolis Hastings Sampling
  • Conditional Random Fields
  • Probabilistic Inference
  • Factor Graphs
  • Expectation Maximization Algorithm

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This repository includes 5 of 9 programming assignments solved while taking up Coursera's Probability Graphical Model course.

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  • C++ 70.5%
  • MATLAB 27.1%
  • Makefile 0.7%
  • Perl 0.7%
  • CSS 0.5%
  • Shell 0.2%
  • Other 0.3%