https://github.com/wangyongjie-ntu/ng-stanford--machine-learning
https://github.com/wangyongjie-ntu/ng-stanford--machine-learning
Last synced: 3 months ago
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- Host: GitHub
- URL: https://github.com/wangyongjie-ntu/ng-stanford--machine-learning
- Owner: wangyongjie-ntu
- Created: 2018-03-03T08:26:17.000Z (about 7 years ago)
- Default Branch: master
- Last Pushed: 2018-04-20T01:57:52.000Z (about 7 years ago)
- Last Synced: 2025-01-09T19:57:41.278Z (4 months ago)
- Language: Matlab
- Size: 21 MB
- Stars: 0
- Watchers: 1
- Forks: 1
- Open Issues: 0
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Metadata Files:
- Readme: readme.md
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README
# Introduce
I created this repository for sharing my programming homework of machine learning course(Ng, Stanford). You can browse it by this [website](https://www.coursera.org/learn/machine-learning/home/welcome). I think this course is very significant and educational for machine learning rookies. Considering not skillful with Matlab, If you find some bugs in my code, do not hesitate to send email to me. I will appreciate it very much.
## ex1 linear regression with multiple variables
I have worked out all the programming tasks(including optional tasks) of week 2 and the results returned from Stanford shows that they are all right.
## ex2 logistic regression
All examples test well(nice work) after submiting.
## ex3 nerual networks:Representation
All examples test well(nice work)
## ex4 neural networks:Learning
All examples test well(nice work)
## ex5 advice for applying machine learning & machine leanring system design
All examples test well.
Need to notice, training error doesnot include the regularization term. You should compute the training error and validation error by setting lambda equals 0 in the validationCurve.m
## ex6 support vector machines
All examples test well.
## ex7 unsupervised learning
All files test well.
PCA for face recognition is very funny. It need more mathmatic methods to provides them.
## ex8 anomaly-detection-and-recommender-systems
all examples is accepted.
# Conclusion
Until now, all programming tasks are finished. Very thanks for NG's great works. I strongly recommand you complete the programing jobs by yourself. and last to speak, it's never late for study this course if you want.
种一棵树最好的时间是十年前，其次是现在!
# Licensing
No complex licenses. Do anything you want.