Introduction of
Machine Learning
2016. 1.4
Dong-Hyun Kwak
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Table of Contents
What is AI? ML?
Various Field in ML
The Special Thing in ML
Polynomial Curve Fitting
Overfitting / Underfitting
Curse of Dimensionality
Training / Test / Validation Error
Cross-validation
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What is AI? ML?
https://www.linkedin.com/pulse/deep-dive-venture-landscape-ai-ajit-nazre-rahul-garg-nazre
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Various Field in ML
https://www.linkedin.com/pulse/how-exceed-your-goals-2016-dr-travis-bradberry-1
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Various Algorithm in ML
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Various Algorithm in ML
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The Special Thing in ML
y = f(x; Θ)
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Function Approximation
http://arxiv.org/pdf/1411.4555.pdf
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https://people.mpi-inf.mpg.de/~kkim/supres/supres.htm
Conventional AI vs ML
http://www.rsipvision.com/exploring-deep-learning/
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Simplest
Example of ML
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Polynomial Curve Fitting
Microsoft Excel 2007의 추세선
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Overfitting / Underfitting
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http://datascience.stackexchange.com/questions/361/when-is-a-model-underfitted
Overfitting / Underfitting
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https://www.researchgate.net/post/How_to_Avoid_Overfitting
Curse of Dimensionality
http://www.newsnshit.com/curse-of-dimensionality-interactive-demo/
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Training / Test / Validation Error
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Training / Test / Validation set
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Validation Dataset
Percentage Split
• Problems
1)
모든 데이터를 학습에 사용
하지 못함.
2)
해당 split에만 운좋게 잘할
수 있음.(Overfitting)
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Cross-validation
http://stackoverflow.com/questions/31947183/how-to-implement-walk-forward-testing-in-sklearn
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The Problem of Cross-validation
• Sequential Data
소리를 들려주고 사람 목소리 vs 자동차 경적소리를 구분하는 문제
라면  랜덤으로 데이터가 섞이는 과정에서 t-1의 데이터를
training에서 학습 후, t의 데이터를 validation에서 평가할 수 있음.
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THANK YOU
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