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Bayesian Statistics: Techniques and Models

by Matthew HeinerTop Instructor
  • 4.8
Approx. 30 hours to complete
In particular, we will introduce Markov chain Monte Carlo (MCMC) methods, which allow sampling from posterior distributions that have no analytical solution. Markov chains Markov chains Markov chain Monte Carlo (MCMC)...
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Probability - The Science of Uncertainty and Data

by John Tsitsiklis , Dimitri Bertsekas , Patrick Jaillet , Karene Chu
  • 0.0
16 Weeks
an introduction to random processes (Poisson processes and Markov chains)...
$300
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Free

Introduction to Graduate Algorithms

by Eric Vigoda , Arpan Chakraborty
  • 0.0
Approx. 3 months
The design and analysis of algorithms form an essential basis for computer science. This course is useful for those who want to pursue advanced studies in computer science, as well as those who want to work as a software engineer. Learn advanced techniques for designing algorithms and apply them to hard computational problems....
Free
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Stochastic processes

by Vladimir Panov
  • 4.5
Approx. 23 hours to complete
Week 3: Markov Chains 1: Definition of a Markov chain. 2: Matrix representation of a Markov chain. Applications of the Markov chains Markov Chains...
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Bayesian Methods for Machine Learning

by Daniil Polykovskiy , Alexander Novikov
  • 4.5
Approx. 33 hours to complete
Markov chain Monte Carlo Markov Chains Markov Chain Monte Carlo summary Markov Chain Monte Carlo...
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Fundamentals of Quantitative Modeling

by Richard Waterman
  • 4.6
Approx. 8 hours to complete
6 Markov Chain Models...
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Statistical Mechanics: Algorithms and Computations

by Werner Krauth
  • 4.8
Approx. 16 hours to complete
Tutorial 8: Ising model - Heat bath algorithm, coupling of Markov chains...
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