PowerPoint Presentation

( ), - DATANADA

2016. 01. 17 16:00~ K 15. @DATANADA, AI Company- Forked from / Seoul National University , / Seoul National University Application , VC .

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. j@jdlab.org

John Park Organizer HP , Kaggle 20 .ADA Framework

: UC /

: IBM Researcher Symantec Security Researcher HP Principle Data Scientist : , ,

: Security Topics in Big Data (HP) Bitcoin and Security (HP)

: Intelligent Hashes for Centralized Malware Detection (US. Patent 2014)

4Issue ? CNN Unsupervised Learning / Reinforcement Learning / RNN

5 CS - MS Researcher, Park **

The Great A.I. Awakening ( ) - NYThttp://www.nytimes.com/2016/12/14/magazine/the-great-ai-awakening.html?_r=0

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71, 2, 3, 4

Steam Engine

Electricity, Automobile

PC, Internet

Artificial Intelligence

?1234

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, , Credit : Nvidia blog

9 , . .

vsEasyHard

10 (?)

11(Machine Learning)(Machine Learning)Machine learningis the subfield ofcomputer sciencethat "gives computers the ability to learn without being explicitly programmed " .

Computer

inputsprogram

outputs

Computer

inputsoutputs

program programming program !

12Quiz ?3 x + 2 x = 11 x + 4 x = -35 x + 5 x = 08 x + 3 x = 5 = 1, = -1

(3, 2), (1, 4), (5, 5), (8, 3) input data, 1, -3, 0, 5 label weight weight

13 Supervised Learning()Input labels (classification), (regression)

Unsupervised Learning()Input (clustering), (compression)

Reinforcement Learning()Label reward Action selection, policy learning

14Perceptron(Artificial Neural Network)

sigmoid activation function

15 (Regression) ()() (km) 1 ()

16 x 2 + x 0.3 + x (-1) + x 0.1 = ()

17 ,,, random ()2 ,,, 1 , ( )2 = 287.524

,,, ()2 0 ,

(Deep Learning)

19(Deep Learning) deep neural network Hidden layer = 2 deep network

weight ??

20 Vanishing gradient problemOverfitting problem