191123 deeplearning day1 copy - blog.kakaocdn.net
TRANSCRIPT
딥-러닝딥러닝,�첫�번째�날�
2019.11.23.
Deep�Learning
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
첫�번째�날
딥러닝�이론�
케라스�
Azure�Cloud�설정�
MLP�생성�(Multi�Layer�Perceptron)
이론�
실습�
두�번째�날
이미지�분류�이론�
Azure�Cloud�GPU�활용�
cifar10�이미지�분류
이론�
실습�
실습�
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
딥-러닝�개론/용어를�이해한다�
MLP�모델을�이해/활용할�수�있다�
이미지�분류�문제를�해결할�수�있다
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
Deep�Learning�
Deep�Neural�Network�
Artificial�Neural�Network(ANN)�
Multi�Layer�Perceptron
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
인공지능
머신러닝
딥러닝
http://bisintek.com/science/2017/12/27/knowing-basic-artificial-intelligence/
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
https://miro.medium.com/max/1200/1*c_fiB-YgbnMl6nntYGBMHQ.jpeg
Data�Driven�Machine�Learning
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
https://www.extremetech.com/wp-content/uploads/2015/12/Brain-Machine-2-640x356.jpghttps://www.alzheimersreadingroom.com/2016/07/alzheimer-tau-protein-spreads-through-brain.html
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
https://blog.siodigital.com/artificial-neural-networks-and-marketing
Multi�Layer�Perceptron
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
Perceptron
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
Frank�Rosenblatt
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
인공�신경
입력1
입력2
입력3
Perceptron
가중치2
가중치1
가중치3
함수출력
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
출력f(x)
인공�신경
x1
x2
x3
w1
w2
w 3
Perceptron
출력
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
출력f(x)인공�신경
x1
x2
x3
w1
w2
w3
Perceptron
출력
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
f(x)
x1
x2
x3
w1
w2
w3
w1x1 + w2x2 + w3x3 + b = ∑ wnxn + b
f∑ wnxn + b
인공�신경 출력
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
f∑ wnxn + b ≥ θ
f∑ wnxn + b < θ
1
0
θ =threshold*
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
https://qbi.uq.edu.au/brain/brain-anatomy/axons-cable-transmission-neurons
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
x
y
1
θ
f∑ wnxn + b
Step�Function
0
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
f∑ wnxn + b ≥ θ
f∑ wnxn + b < θ
1
0
Linear�Binary�Classifier
θ =threshold*
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
https://miro.medium.com/max/1624/1*xsR57_PO8U7PB_ItLslLmA.png
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
0�or�10�or�1
AND�Function
AND�Gatex2
0�or�1
0�or�1
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
AND�Function
0 0
AND
0
0 1 0
1 0 0
1 1 1
x1 x2 f(x) y
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
x1
x2
1
1
0
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
XOR�Function
0 0
XOR
0
0 1 1
1 0 1
1 1 0
x1 x2 f(x) y
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
0�or�1
XOR�Function
XOR�Gatex2
0�or�1
0�or�1
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
x1
x2
1
1
0
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
x1
x2
1
1
0
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
0�or�1ANDx2
0�or�1
0�or�1ORx2
0�or�1
0�or�1 NOT�ANDx2
0�or�1
0�or�1
0�or�1
0�or�1
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
Multi�Layer�Perceptron(MLP)
x2
0�or�1
0�or�1
0�or�1
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
https://blog.siodigital.com/artificial-neural-networks-and-marketing
Multi�Layer�Perceptron
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
How�it�works?
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
Weight�Initialization�
Forward�Propagation�
Back�Propagation
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
0�or�11x2
0
1
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
Weight�Initialization
wj = [[−10,10], [20, − 20], [5, − 10]] wk = [−20,10, − 20]
x2
0
1
1
wj1
wj2
wj3
wj4
wj5
wj6
wj7
wj8
wj9
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
Forward�Propagation
wj = [[−10,10], [20, − 20], [5, − 10]] wk = [−20,10, − 20]
x2
0
1
10
-20
-10
1
wj1
wj2
wj3
wj4
wj5
wj6
wj7
wj8
wj9
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
x
y
1
θ
f∑ wnxn + b
Step�Function
0
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
Forward�Propagation
wj = [[−10,10], [20, − 20], [5, − 10]] wk = [−20,10, − 20]
1
x20
0
0
1
10
-20
-10
1
wj1
wj2
wj3
wj4
wj5
wj6
wj7
wj8
wj9
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
Forward�Propagation
wj = [[−10,10], [20, − 20], [5, − 10]] wk = [−20,10, − 20]
1
x20
0
0
1
10
-20
-10
1
0-20
wj1
wj2
wj3
wj4
wj5
wj6
wj7
wj8
wj9
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
차이�비교
wj = [[−10,10], [20, − 20], [5, − 10]] wk = [−20,10, − 20]
1
x20
0
0
1
10
-20
-10
1
0-20
wj1
wj2
wj3
wj4
wj5
wj6
wj7
wj8
wj9
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
1
x20
0
0
1
Back�Propagation
wj = [[−10,10], [20, − 20], [5, − 10]]
10
-20
-10
1
wk = [−20,10, − 20]
0-20
wk = [10, − 10,15]wj = [[5, − 20], [−30,10], [−15,20]]
wj1
wj2
wj3
wj4
wj5
wj6
wj7
wj8
wj9
UPDATE
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
Weight�Initialization�
Forward�Propagation�
비교�
Back�Propagation
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
차이�비교
wj = [[−10,10], [20, − 20], [5, − 10]] wk = [−20,10, − 20]
1
x20
0
0
1
10
-20
-10
1
0-20
wj1
wj2
wj3
wj4
wj5
wj6
wj7
wj8
wj9
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
Cost�Function
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
예측�값과�실제�값의�차이를�기반으로��
모델의�정확도(성능)을�판단하기�위한�함수
Cost�Function *�loss�function�
*�error�function�
*�objective�function
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
J(w, b) =1n
n
∑i
(h(xi)) − yi)2
mean�squared�error
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
w, b
J(w, b)
0
Gradient�Descent�
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
w, b
J(w, b)
0
Gradient�Descent�
w = w − αδ
δwJ(w)
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
Optimizer어떻게?
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
http://www.cs.toronto.edu/~tijmen/csc321/slides/lecture_slides_lec6.pdf
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
Optimizer
https://ruder.io/optimizing-gradient-descent/
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
https://ruder.io/optimizing-gradient-descent/
Optimizer
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
https://www.slideshare.net/yongho/ss-79607172
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
Optimizer
Perceptron MLP
Weight�InitializationForward�Propagation
Back�PropagationCost�Function
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
Overfitting
Vanishing�Gradient
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
f(x)
x1
x2
x3
w1
w2
w3
w1x1 + w2x2 + w3x3 + b = ∑ wnxn + b
f∑ wnxn + b
인공�신경 출력
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
x
y
1
θ
f∑ wnxn + b
Step�Function
0
https://theffork.com/activation-functions-in-neural-networks/
Sigmoid�Function
https://ayearofai.com/rohan-4-the-vanishing-gradient-problem-ec68f76ffb9b
http://skymind.ai/wiki
https://medium.com/@anishsingh20/the-vanishing-gradient-problem-48ae7f501257
https://theffork.com/activation-functions-in-neural-networks/
Sigmoid
https://theffork.com/activation-functions-in-neural-networks/
ReLU�Rectified�Linear�Unit
https://theffork.com/activation-functions-in-neural-networks/
tanh
https://theffork.com/activation-functions-in-neural-networks/
Leakey�ReLU
https://www.quora.com/Why-is-ReLU-the-most-common-activation-function-used-in-neural-networks
https://theffork.com/activation-functions-in-neural-networks/
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
Overfitting
Vanishing�Gradient
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
Model�Capacity
x
yy = ax + b
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
Model�Capacity
x
yy = ax + b
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
x
yy = ax + b
y = k + ax0 + bx1 + cx2
https://youtu.be/_sz3KTyB9Lk
https://youtu.be/_sz3KTyB9Lk
https://youtu.be/_sz3KTyB9Lk
https://hackernoon.com/memorizing-is-not-learning-6-tricks-to-prevent-overfitting-in-machine-learning-820b091dc42
Regularization
https://i.stack.imgur.com/CewjH.png
Dropout
https://deepestdocs.readthedocs.io/en/latest/004_deep_learning_part_2/image/0042_fig0.jpg
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
케라스, 뭔가요?
Keras
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
AI�접근성과�민주화� 딥러닝의�대중화�
Keras�
François�Chollet
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
- 파이썬으로�구현된�high-level�deep�learning�API�
- TesnsorFlow,�Theano,�CNTK�
- 쉬운�사용법과�간단한�문법,�빠른�설계�가능
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
김태영의 케라스 블로그: https://tykimos.github.io/
뿔 진실
상아 거짓
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
김태영의 케라스 블로그: https://tykimos.github.io/
우리가 만든 모델이 진실을 말해주길…
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
https://t1.daumcdn.net/cfile/tistory/99BB78335993E64726
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
Keras
https://towardsdatascience.com/deep-learning-framework-power-scores-2018-23607ddf297a
Model�모델
블록과 함께하는 파이썬 딥러닝 케라스, (주)인스페이스 기술이사 김태영
Model�모델
블록과 함께하는 파이썬 딥러닝 케라스, (주)인스페이스 기술이사 김태영
네트워크�network
목표함수�objective�function
최적화기�optimizer
Model�모델
블록과 함께하는 파이썬 딥러닝 케라스, (주)인스페이스 기술이사 김태영
Network�네트워크
Objective�Function�목표함수
Optimizer�최적화기
블록과 함께하는 파이썬 딥러닝 케라스, (주)인스페이스 기술이사 김태영
Network�네트워크
블록과 함께하는 파이썬 딥러닝 케라스, (주)인스페이스 기술이사 김태영
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
x2
0
1
1
wj1
wj2
wj3
wj4
wj5
wj6
wj7
wj8
wj9
Network�네트워크
블록과 함께하는 파이썬 딥러닝 케라스, (주)인스페이스 기술이사 김태영
256
1024
512
784
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네�트�워�크
블록과 함께하는 파이썬 딥러닝 케라스, (주)인스페이스 기술이사 김태영
0
1
블록과 함께하는 파이썬 딥러닝 케라스, (주)인스페이스 기술이사 김태영
https://keras.io/applications/
● Xception (88 MB, 126) ● VGG16 (528 MB, 23) ● VGG19 (549 MB, 26) ● ResNet50 (99 MB, 168) ● InceptionV3 (92 MB, 159) ● InceptionResNetV2 (215 MB, 572) ● MobileNet (17 MB, 88) ● DenseNet121 (33 MB, 121) ● DenseNet169 (57 MB, 169) ● DenseNet201 (80 MB, 201) ● NASNet
InceptionResNet
V2
Xception VGG16 VGG19
ResNet50
InceptionV3
MobileNet
Dense Net
NASNet
Objective�Function�목표함수
블록과 함께하는 파이썬 딥러닝 케라스, (주)인스페이스 기술이사 김태영
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
예측�값과�실제�값의�차이를�기반으로��
모델의�정확도(성능)을�판단하기�위한�함수
Cost�Function *�loss�function�
*�error�function�
*�objective�function
https://keras.io/losses/�
● mean_squared_error�● mean_absolute_error�● mean_absolute_percentage_error�● mean_squared_logarithmic_error�● squared_hinge�● hinge�● categorical_hinge�● logcosh�● categorical_crossentropy�● sparse_categorical_crossentropy�● binary_crossentropy�● kullback_leibler_divergence�● poisson�● cosine_proximity
블록과 함께하는 파이썬 딥러닝 케라스, (주)인스페이스 기술이사 김태영
mean�squared�
categorical� binary�
블록과 함께하는 파이썬 딥러닝 케라스, (주)인스페이스 기술이사 김태영
Optimizer�최적화기
블록과 함께하는 파이썬 딥러닝 케라스, (주)인스페이스 기술이사 김태영
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
https://ruder.io/optimizing-gradient-descent/
Optimizer
https://keras.io/optimizers/�
● SGD�● RMSprop�● Adagrad�● Adadelta�● Adam�● Adamax�● Nadam�● TFOptimizer
블록과 함께하는 파이썬 딥러닝 케라스, (주)인스페이스 기술이사 김태영
블록과 함께하는 파이썬 딥러닝 케라스, (주)인스페이스 기술이사 김태영
https://keras.io/optimizers/�
● SGD�● RMSprop�● Adagrad�● Adadelta�● Adam�● Adamax�● Nadam�● TFOptimizer
SGD RMSprop Adagrad Adam
블록과 함께하는 파이썬 딥러닝 케라스, (주)인스페이스 기술이사 김태영
블록과 함께하는 파이썬 딥러닝 케라스, (주)인스페이스 기술이사 김태영
Compile�컴파일
Network�네트워크
Objective�Function�목표함수
Optimizer�최적화기
블록과 함께하는 파이썬 딥러닝 케라스, (주)인스페이스 기술이사 김태영
Compile�컴파일
Network�네트워크
Objective�Function�목표함수
Optimizer�최적화기
네트워크�network
목표함수�objective�function
최적화기�optimizer
Model�모델
블록과 함께하는 파이썬 딥러닝 케라스, (주)인스페이스 기술이사 김태영
adam
binary
블록과 함께하는 파이썬 딥러닝 케라스, (주)인스페이스 기술이사 김태영
sgd
categorical
블록과 함께하는 파이썬 딥러닝 케라스, (주)인스페이스 기술이사 김태영
블록과 함께하는 파이썬 딥러닝 케라스, (주)인스페이스 기술이사 김태영
𝑿 𝒀
블록과 함께하는 파이썬 딥러닝 케라스, (주)인스페이스 기술이사 김태영
𝑿 𝒀𝒀 '
블록과 함께하는 파이썬 딥러닝 케라스, (주)인스페이스 기술이사 김태영
𝑿
𝒀 ' 𝒀
𝒀𝒀 '
블록과 함께하는 파이썬 딥러닝 케라스, (주)인스페이스 기술이사 김태영
𝑿
𝒀 ' 𝒀
𝒀𝒀 '
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
첫�번째�날
딥러닝�이론�
케라스�
Azure�Cloud�설정�
MLP�생성�(Multi�Layer�Perceptron)
이론�
실습�
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
AI�Service�On�Azure�Cloud�
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
DSVM
https://azure.microsoft.com/en-us/services/virtual-machines/data-science-virtual-machines//?WT.mc_id=AI-MVP-5003262
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
https://azure.microsoft.com/en-us/services/virtual-machines/data-science-virtual-machines//?WT.mc_id=AI-MVP-5003262
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
Before�we�run,
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
Resource�Group�
Resource�
Subscription�
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
Resource�
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
Region�
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
https://azure.microsoft.com/en-us/global-infrastructure/regions/
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
https://azure.microsoft.com/en-us/global-infrastructure/regions/
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
Region East�US
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
Resource�Group�
Resource�
Subscription�
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
Region Korea�Central
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
Resource�Group�
Resource�
Subscription�
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
Pay�As�You�Go
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
Resource�Group�
Resource�
Subscription�
Virtual�Machine
AzureClass2324
AI_GroupKorea�Central
East�West2
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
Let’s�Strat�HOL�💻
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
데이터�셋�준비
문제�정의
모델�설정
모델�훈련�/�평가
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
AND��Function
1번�문제�정의
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
0�or�10�or�1
AND�Function
AND�Gatex2
0�or�1
0�or�1
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
AND�Function
0 0
AND
0
0 1 0
1 0 0
1 1 1
x1 x2 f(x) y
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
�XOR��Function
2번�문제�정의
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
XOR�Function
0 0
XOR
0
0 1 1
1 0 1
1 1 0
x1 x2 f(x) y
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
0�or�1
XOR�Function
XOR�Gatex2
0�or�1
0�or�1
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
�당뇨병�발병�예측�
3번�문제�정의
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
Pima�Indian�Diabets
https://www.researchgate.net/figure/Pima-Indian-Diabetes-dataset-attributes_tbl1_325653625
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
Activation�Layers
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
은닉층�(Hidden�Layer)
ReLU Leaky�ReLu ELU
Rectifier�linear Leaky�ReLUExponential�Linear�Units
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
출력층�(Output�Layer)
linear sigmoid softmax
특정�값��예측
이진�클래스��예측
다중�클래스��예측
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
Data
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
batch_size
X_train Y_train
문제�몇개를�풀고�답을�확인�할�것인가?
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
epochs
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
epochs문제를�총�몇번�풀�것인가?
………
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
만일,�
epoch=100,000�
정확도가�100%�되지�않을까??��
😏
Overfitting
https://hackernoon.com/memorizing-is-not-learning-6-tricks-to-prevent-overfitting-in-machine-learning-820b091dc42
https://static1.squarespace.com/static/5213a664e4b01a5565dc90f1/t/5bc4e0c4e4966bc550291202/1546736393368/Machine+Learning+Generalization
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
Data
X_train
X_test
Y_train
Y_test
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
Data
X_train
X_test
Y_train
Y_test
X_val Y_val
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
https://hackernoon.com/memorizing-is-not-learning-6-tricks-to-prevent-overfitting-in-machine-learning-820b091dc42
epoch
loss
Loss�Function
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
우리도�할�수�있어요,�
딥-러닝�🥳
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
Keras
케라스�문서�
같은�결과가�나오도록�학습하는�방법�
30초만에�케라스�시작하기�
케라스�튜토리얼(한글)�
김태영님의�케라스�강의(한글)�
케라스�코리아(페이스북)
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
Data�Science�Virtual�Machine
DSVM�이란?�
DSVM�DeepLearning�VM�생성하기�
Linux�및�Windows용�DSVM�소개�
DSVM�딥러닝�프레임워크�
�DSVM�데이터�수집도구�
Linux�DSVM�사용하기
2019.11.23.�|�한이음�ICT�멘토링�|�딥러닝�특강1�|�전미정
What the hell is perceptron
From perceptron to deep neural nets
Neural�Networks�6:�solving�XOR�with�a�hidden�layer
Optimizing-gradient-descent
Activation�functions�in�neural�networks
DeepLearning