# 10-601 Naive Bayes

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Jump to navigationJump to searchThis a lecture used in the Syllabus for Machine Learning 10-601B in Spring 2016

### Slides and Other Materials

- Catchup - MAP and Joint Distribution: Slides in Powerpoint, Slides in PDF
- Main lecture: Slides in Powerpoint, Slides in PDF

### Readings

- Mitchell 6.1-6.10
- Murphy 3
- My favorite on-line Matlab docs

### What You Should Know Afterward

- What conditional independence means
- How to implement the multinomial Naive Bayes algorithm
- How to interpret the predictions made by the NB algorithm