Introduction to Programming - Jun Jijun.hansung.ac.kr/ML/docs-slides-Lecture8-kr.pdf ·...
Transcript of Introduction to Programming - Jun Jijun.hansung.ac.kr/ML/docs-slides-Lecture8-kr.pdf ·...
신경망(Neural Networks): 표현
비선형모델
Machine Learning
Andrew Ng
비선형분류
x1
x2
size# bedrooms# floorsage
Andrew Ng
당신은이것을봅니다:
그러나카메라는이것을봅니다:
이것은무엇인가?
Andrew Ng
Computer Vision: 자동차감지
Testing:
What is this?
Not a carCars
Andrew Ng
Learning Algorithm
pixel 1
pixel 2
pixel 1
pixel 2
Raw image
Cars“Non”-Cars
Andrew Ng
pixel 1
pixel 2
Raw image
Cars“Non”-Cars
Learning Algorithm
pixel 1
pixel 2
Andrew Ng
pixel 1
pixel 2
Raw image
Cars“Non”-Cars
50 x 50 pixel images→ 2500 pixels(7500 if RGB)
pixel 1 intensity
pixel 2 intensity
pixel 2500 intensity
Quadratic features ( ): ≈3 millionfeatures
Learning Algorithm
pixel 1
pixel 2
Andrew Ng
신경망(Neural Networks): 표현
신경과뇌
Machine Learning
Andrew Ng
신경망(Neural Networks)
기원: 뇌를모방하기위한알고리즘.
80년대와 90년대초에절리사용되었음; 90년대후반에감소.
최근제기: 많은응용분야에서의첨단기술
Andrew Ng
청각피질이시각을학습한다.
청각피질(Auditory Cortex)
“학습알고리즘” 가설(hypothesis)
[Roe et al., 1992]
Andrew Ng
체성감각피질이시각을학습한다.
체성감각피질(Somatosensory Cortex)
The “one learning algorithm” hypothesis
[Metin & Frost, 1989]
Andrew Ng
혀로보기 사람반향위치측정 (음파탐지기:sonar)
촉각띠(Haptic belt): 방향감지 3번째눈심기
뇌에서의감각표현
[BrainPort; Welsh & Blasch, 1997; Nagel et al., 2005; Constantine-Paton & Law, 2009]
Neural Networks: Representation
Machine Learning
모델표현 I
Andrew Ng
뇌속의신경들
수상돌기
축색돌기
세포체
Andrew Ng
뇌속의신경들
[Credit: US National Institutes of Health, National Institute on Aging]
Andrew Ng
신경모델: 로지스틱(Logistic)단위
시그모이드(로지스틱) 활성함수
Sigmoid (logistic) activation function.
Andrew Ng
Neural Network
Layer 3Layer 1 Layer 2
Andrew Ng
Neural Network“activation” of unit in layer
matrix of weights controlling function mapping from layer to layer
If network has units in layer , units in layer , thenwill be of dimension .
Andrew Ng
Neural Networks: Representation
모델표현 II
Machine Learning
Andrew Ng
Add .
전방향전파: 백터화구현
Andrew Ng
Layer 3Layer 1 Layer 2
Neural Network learning its own features
Andrew Ng
Layer 3Layer 1 Layer 2
Other network architectures
Layer 4
Neural Networks: Representation
Examples and intuitions I
Machine Learning
Andrew Ng
비선형분류예 : XOR/XNOR
, 는이진수(binary) (0 or 1).
x1
x2
x1
x2
Andrew Ng
Simple example: AND
0 00 11 01 1
1.0
Andrew Ng
Example: OR function
0 00 11 01 1
-10
20
20
Neural Networks: Representation
Examples and intuitions II
Machine Learning
Andrew Ng
부정(Negation):
01
Andrew Ng
Andrew Ng
Putting it together:
0 00 11 01 1
-30
20
20
10
-20
-20
-10
20
20
Andrew Ng
Neural Network intuition
Layer 3Layer 1 Layer 2 Layer 4
Andrew Ng
Handwritten digit classification
[Courtesy of Yann LeCun]
Andrew Ng
Handwritten digit classification
[Courtesy of Yann LeCun]
Andrew Ng
Neural Networks: Representation
Multi-class classification
Machine Learning
Andrew Ng
Multiple output units: One-vs-all.
Pedestrian Car Motorcycle Truck
Want , , , etc.
when pedestrian when car when motorcycle
Andrew Ng
Multiple output units: One-vs-all.
Want , , , etc.
when pedestrian when car when motorcycle
Training set:
one of , , ,
pedestrian car motorcycle truck
Andrew Ng