1. %ìÝ(Deep Learning)
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September 10, 2014
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2. What is Deep Learning?
Contents
1 What is Deep Learning?
2 History
Perceptron
Multilayer Perceptron
1st Breakthrough: Unsupervised Learning
2nd Breakthrough: Supervised Learning
3 Apply to Public Health
Epidemiology vs Machine Learning
Deep Learning vs Other ML
Hypothesis Testing vs Hypothesis Generating
4 Conclusion
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3. What is Deep Learning?
Machine Learning
ôè0 YµXì !` ˆÄ] !¨(prediction)D
X” xõÀ¥X „|.
Computer science + Statistics ??
Amazon, Google, Facebook..
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4. What is Deep Learning?
Neural Network
Human brain VS Computer
3431 3324 =??
@ à‘t lÄ, L1xÝ, 8xÝ
Sequential VS Parallel
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5. What is Deep Learning?
Neuron Arti

6. cial Neural Network(ANN)[19]
Figure. (A) Human neuron; (B) arti

7. cial neuron or hidden unity; (C) biological
synapse; (D) ANN synapses.
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8. What is Deep Learning?
http://www.nd.com/welcome/whatisnn.htm
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9. What is Deep Learning?
Deep Neural Network(DNN) ' Deep Learning
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10. What is Deep Learning?
Œ IT0Å `0ÄYµ' Ñ http://www.dt.co.kr/contents.
html?article_no=2014062002010960718002
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http://vip.mk.co.kr/news/view/21/20/1178659.html
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http://www.bloter.net/archives/196341
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http://www.wikitree.co.kr/main/news_view.php?id=157174
xõÀ¥ Ü lX èt¼ ¸ http://weekly.chosun.
com/client/news/viw.asp?nNewsNumb=002311100009ctcd=C02
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11. History
Contents
1 What is Deep Learning?
2 History
Perceptron
Multilayer Perceptron
1st Breakthrough: Unsupervised Learning
2nd Breakthrough: Supervised Learning
3 Apply to Public Health
Epidemiology vs Machine Learning
Deep Learning vs Other ML
Hypothesis Testing vs Hypothesis Generating
4 Conclusion
@Ä- ( ´íY) %ìÝ(Deep Learning) September 10, 2014 9 / 74

12. History Perceptron
Perceptron
1958D Rosenblatt[23].
y = '(
Xn
i=1
wi xi + b) (1)
(b: bias, ': activation function(e.g: logistic or tanh))
Figure. Concept of Perceptron[Honkela]
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13. History Perceptron
Low Performance
XORÄ t°XÀ »ä[Hinton].
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14. History Multilayer Perceptron
Multilayer Perceptron
Hidden layer| ˜¬t t°ä!!
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15. History Multilayer Perceptron
Learing Problem
Hidden layer ! Weight / ..
1985D: Error Backpropagation Algorithm[24]
Gradient Descent Methods
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16. History Multilayer Perceptron
Gradient Descent Methods
Weight /