Difference between revisions of "Class meeting for 10-605 Probability Review"
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* [http://www.cs.cmu.edu/~wcohen/10-605/prob-tour+bayes.pptx Slides in Powerpoint] | * [http://www.cs.cmu.edu/~wcohen/10-605/prob-tour+bayes.pptx Slides in Powerpoint] | ||
| + | * [http://www.cs.cmu.edu/~wcohen/10-605/prob-tour+bayes.pdf Slides in PDF] | ||
=== Readings for the Class === | === Readings for the Class === | ||
Latest revision as of 17:46, 30 August 2017
This is one of the class meetings on the schedule for the course Machine Learning with Large Datasets 10-605 in Fall 2017.
Slides
Readings for the Class
- Optional: Mitchell 6.1-6.10
Today's quiz
Things to remember
- The joint probability distribution
- Brute-force estimation of a joint distribution
- Density estimation and how it can be used for classification
- Naive Bayes and the conditional independence assumption
- Asymptotic complexity of naive Bayes
- What are streaming machine learning algorithms: ML algorithms that never load in the data
