About this Course

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Advanced Level
Approx. 21 hours to complete
English
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Advanced Level
Approx. 21 hours to complete
English

Offered by

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University of California, Santa Cruz

Syllabus - What you will learn from this course

Week
1

Week 1

4 hours to complete

Basic concepts on Mixture Models

4 hours to complete
9 videos (Total 94 min), 7 readings, 9 quizzes
9 videos
Installing and using R5m
Basic definitions25m
Mixtures of Gaussians10m
Zero-inflated mixtures11m
Hierarchical representations7m
Sampling from a mixture model5m
The likelihood function14m
Parameter identifiability10m
7 readings
An Introduction to R45m
Example of a bimodal mixture of Gaussians3m
Example of a unimodal and skewed mixture of Gaussians3m
Example of a unimodal, symmetric and heavy tailed mixture of Gaussians3m
Example of a zero-inflated negative binomial distribution3m
Example of a zero-inflated log Gaussian distribution3m
Sample code for simulating from a Mixture Model10m
7 practice exercises
Basic definitions6m
Mixtures of Gaussians4m
Zero-inflated distributions4m
Definition of Mixture Models20m
The likelihood function
Identifiability
Likelihood function for mixture models4m
Week
2

Week 2

4 hours to complete

Maximum likelihood estimation for Mixture Models

4 hours to complete
4 videos (Total 73 min), 2 readings, 2 quizzes
4 videos
EM for location mixtures of Gaussians22m
EM example 112m
EM example 213m
2 readings
Sample code for EM example 110m
Sample code for EM example 210m
Week
3

Week 3

4 hours to complete

Bayesian estimation for Mixture Models

4 hours to complete
6 videos (Total 84 min), 2 readings, 2 quizzes
6 videos
Markov Chain Monte Carlo algorithms, part 213m
MCMC for location mixtures of normals Part 119m
MCMC for location mixtures of normals Part 214m
MCMC Example 111m
MCMC Example 211m
2 readings
Sample code for MCMC example 110m
Sample code for MCMC example 210m
Week
4

Week 4

5 hours to complete

Applications of Mixture Models

5 hours to complete
7 videos (Total 108 min), 3 readings, 3 quizzes
7 videos
Density Estimation Example10m
Mixture Models for Clustering23m
Clustering example11m
Mixture Models and naive Bayes classifiers21m
Linear and quadratic discriminant analysis in the context of Mixture Models18m
Classification example10m
3 readings
Sample code for density estimation problems10m
Sample EM algorithm for clustering problems10m
Sample EM algorithm for classification problems10m

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