(Video + graphics and text) introduction to machine learning series - Chapter 4 naive Bayes

Introduction to machine learning series , Mr. Huang haiguang . This site will be continuously updated ,ppt、 Code 、 See the end of the text for the exercises after class .

The catalogue of this series

01. introduction

02. Return to

03. Logical regression

04. Naive Bayes

05. Machine learning practice

06. Machine learning library Scikit-learn

07.KNN Algorithm

08. Decision tree

09. Integrated learning

10. Artificial neural network

11. Support vector machine

12. clustering

13. Dimension reduction

14. Association rules

15. Machine learning project process

Contents of this chapter

• 4.1 Bayesian method

• 4.2 Naive Bayes principle

• 4.3 Naive Bayes case

• 4.4 Naive Bayesian code implementation

4.1 Bayesian method

Video Explanation

Graphic content

4.2 Naive Bayes principle

Video Explanation

Graphic content

3.3 Naive Bayes case

Video Explanation

Graphic content

4.4 Naive Bayesian code implementation

Video Explanation

Graphic content

Related resources

The course threshold is low , As long as you have mathematics knowledge above the third grade of undergraduate course , Know a programming language , You can master most of the content of this course .

Course link （ Chinese University MOOCS , There are exercises and certificates ）：
https://www.icourse163.org/course/WZU-1464096179

Course resources （pdf Version courseware and code ） Published in Github：

https://github.com/fengdu78/WZU-machine-learning-course

Course videos can also be found in b Stand and watch （ Convenient viewing , But there are no after-school exercises and certificates ）：

https://www.bilibili.com/video/BV1gP4y177cf?share_source=copy_web

  If it's a school teacher , Please tell us the name of the school , I can send the original ppt file , Please use edu Contact me via email ：[email protected]

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