Overview
Context of the Mixture Models in R course at Data Camp
Mixture modeling is a way of representing populations when we are interested in their heterogeneity. Mixture models use familiar probability distributions (e.g. Gaussian, Poisson, Binomial) to provide a convenient yet formal statistical framework for clustering and classification.
Unlike standard clustering approaches, we can estimate the probability of belonging to a cluster and make inference about the sub-populations.
For example, in the context of marketing, you may want to cluster different customer groups and find their respective probabilities of purchasing specific products to better target them with custom promotions.
When applying natural language processing to a large set of documents, you may want to cluster documents into different topics and understand how important each topic is across each document.
Programme Structure
Chapters
- Structure of Mixture Models and Parameters Estimation
- Mixture of Gaussians with `flexmix`
- Mixture Models Beyond Gaussians
Key information
Duration
- Part-time
- 1 days
Start dates & application deadlines
Language
Delivered
Disciplines
Information Technology (IT) Computer Sciences View 384 other Short Courses in Information Technology (IT) in United StatesAcademic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
PREREQUISITES
- Intermediate R
- Introduction to the Tidyverse
- Foundations of Probability in R
Tuition Fee
-
International
FreeTuition FeeBased on the tuition of 0 USD for the full programme during 1 days. -
National
FreeTuition FeeBased on the tuition of 0 USD for the full programme during 1 days.
Basic Access: Free; Premium (for individuals): $12.42 per month billed annually; Teams: $25 per month billed annually; Enterprise: Contact sales for pricing