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<title>Machine Learning (2017, Spring)</title>
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# Bonus: Semi-supervied Learning
Problem Description:
* Remove some label in training data as **unlabeled data**
* Implement semi-supervised learning algorithm such as self-training, clustering
* Compare the performance with the model using only the labeled training data, record the training procedure
## Lecture
<img src="semi.png" alt="Drawing" style="width: 800px;"/>
## Reference:
→ http://speech.ee.ntu.edu.tw/~tlkagk/courses/ML_2016/Lecture/semi%20(v3).pdf
→ [More Semi-supervised Learning Tutorial](http://pages.cs.wisc.edu/~jerryzhu/pub/sslicml07.pdf)
→ [上學期 Machine Learning 作業三的說明](http://speech.ee.ntu.edu.tw/~tlkagk/courses/ML_2016/Lecture/ML%20HW3.pdf)
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<center><i class="fa fa-github"></i></a> Posted by: <a href="https://github.com/sunprinceS/" target="_blank">sunprinceS</a> </center>
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<center><i class="fa fa-mortar-board"></i> Course information: <a href="http://speech.ee.ntu.edu.tw/~tlkagk/courses_ML17.html", target="_blank">Machine Learning (2017, Spring) @ National Taiwan University</a>.</center>
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