- Probability & Statistics
- Statistical Methods
- Probability Distribution
- Mathematical Modeling
- Classification Algorithms
- Unsupervised Learning
- Bayesian Statistics
- R Programming
- Machine Learning Methods
- Statistical Modeling
- Markov Model
- Statistical Software
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
