Bayesian Statistics: Mixture Models introduces you to an important class of statistical models. The course is organized in five modules, each of which contains lecture videos, short quizzes, background reading, discussion prompts, and one or more peer-reviewed assignments. Statistics is best learned by doing it, not just watching a video, so the course is structured to help you learn through application.
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Bayesian Statistics: Mixture Models
This course is part of Bayesian Statistics Specialization
![Abel Rodriguez](https://d3njjcbhbojbot.cloudfront.net/api/utilities/v1/imageproxy/https://coursera-instructor-photos.s3.amazonaws.com/b6/d713106e6911e88e8ddb75c504fdcd/Rodriguez_4710-crop.jpg?auto=format%2Ccompress&dpr=1&w=75&h=75&fit=crop)
Instructor: Abel Rodriguez
10,191 already enrolled
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(60 reviews)
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What you'll learn
Explain the basic principles behind the algorithm for fitting a mixture model.
Compute the expectation and variance of a mixture distribution.
Use mixture models to solve classification and clustering problems, and to provide density estimates.
Skills you'll gain
Details to know
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11 assignments
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There are 5 modules in this course
This module defines mixture models, discusses its properties, and develops the likelihood function for a random sample from a mixture model that will be the basis for statistical learning.
What's included
9 videos7 readings7 assignments2 peer reviews1 discussion prompt
What's included
4 videos2 readings2 peer reviews1 discussion prompt
What's included
6 videos2 readings2 peer reviews
What's included
7 videos3 readings3 peer reviews
What's included
7 videos5 readings4 assignments1 peer review1 discussion prompt
Instructor
![Abel Rodriguez](https://d3njjcbhbojbot.cloudfront.net/api/utilities/v1/imageproxy/https://coursera-instructor-photos.s3.amazonaws.com/b6/d713106e6911e88e8ddb75c504fdcd/Rodriguez_4710-crop.jpg?auto=format%2Ccompress&dpr=1&w=75&h=75&fit=crop)
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Learner reviews
60 reviews
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Reviewed on Feb 10, 2023
I really enjoyed this course! Plenty of examples on how to use Mixture Models in a Machine Learning context. Thanks to Abel and his team for putting together such an useful course.
Reviewed on Jan 19, 2021
I learned a lot about bayesian mixture model, expectation maximization, and MCMC algorithms and their use case in classification and clustering problems. I highly recommend this course.
Reviewed on Apr 13, 2023
Excellent course to illustrate the model step by step. I like the process of derivation.
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