- Markov Model
- Mathematical Modeling
- Probability & Statistics
- Statistical Modeling
- Bayesian Statistics
- Machine Learning Algorithms
- Statistical Software
- Statistical Methods
- Unsupervised Learning
- R Programming
Bayesian Statistics: Mixture Models
Completed by Francisco Santos da Silva
May 21, 2021
21 hours (approximately)
Francisco Santos da Silva's account is verified. Coursera certifies their successful completion of Bayesian Statistics: Mixture Models
What you will 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 will gain
