University of California, Santa Cruz

Bayesian Statistics: Mixture Models

This course is part of Bayesian Statistics Specialization

Taught in English

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Abel Rodriguez

Instructor: Abel Rodriguez

8,600 already enrolled

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Course

Gain insight into a topic and learn the fundamentals

4.5

(52 reviews)

Intermediate level

Recommended experience

21 hours (approximately)
Flexible schedule
Learn at your own pace

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.

Details to know

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Assessments

11 quizzes

Course

Gain insight into a topic and learn the fundamentals

4.5

(52 reviews)

Intermediate level

Recommended experience

21 hours (approximately)
Flexible schedule
Learn at your own pace

See how employees at top companies are mastering in-demand skills

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This course is part of the Bayesian Statistics Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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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 quizzes2 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 quizzes1 peer review1 discussion prompt

Instructor

Instructor ratings
4.8 (22 ratings)
Abel Rodriguez
University of California, Santa Cruz
1 Course8,600 learners

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4.5

52 reviews

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4

Reviewed on May 17, 2021

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