ML 튜토리얼
Studio 튜토리얼
ML 함수도움말
Studio 함수도움말
라이브러리 검색
옵션
대소문자 구분
유형
전체
제목
코드
표
그림
본문
파트 I.
I/O
1.
DLLoad
1.1
Format
1.2
Description
1.3
Properties
1.4
Constraints
1.5
Example
2.
Image Data Generator
2.1
Format
2.2
Description
2.3
Properties
2.4
Constraints
2.5
Example
3.
Output
3.1
Format
3.2
Description
3.3
Properties
3.4
Constraints
3.5
Example
파트 II.
Core Layer
1.
Dense
1.1
Format
1.2
Description
1.3
Properties
1.4
Constraints
1.5
Example
2.
Activation
2.1
Format
2.2
Description
2.3
Properties
2.4
Constraints
2.5
Example
3.
Dropout
3.1
Format
3.2
Description
3.3
Properties
3.4
Constraints
3.5
Example
4.
Flatten
4.1
Format
4.2
Description
5.
PythonScript
5.1
Format
5.2
Description
5.3
Properties
5.4
Constraints
5.5
Example
6.
Reshape
6.1
Format
6.2
Description
6.3
Properties
6.4
Constraints
6.5
Example
7.
Lambda
7.1
Description
7.2
Properties
7.3
Constraints
7.4
Example
파트 III.
Convolution Layer
1.
Convolution 1D
1.1
Description
1.2
Properties
1.3
Constraints
1.4
Example
2.
Convolution 2D
2.1
Format
2.2
Description
2.3
Properties
2.4
Constraints
2.5
Example
3.
Convolution 3D
3.1
Description
3.2
Properties
3.3
Constraints
3.4
Example
4.
Convolution 2D Transpose
4.1
Description
4.2
Properties
4.3
Constraints
4.4
Example
5.
Separable Conv2D
5.1
Description
5.2
Properties
5.3
Constraints
5.4
Example
6.
ZeroPadding1D
6.1
Description
6.2
Properties
6.3
Constraints
6.4
Example
7.
ZeroPadding2D
7.1
Description
7.2
Properties
7.3
Constraints
7.4
Example
8.
ZeroPadding3D
8.1
Description
8.2
Properties
8.3
Constraints
8.4
Example
9.
Cropping1D
9.1
Description
9.2
Properties
9.3
Constraints
9.4
Example
10.
Cropping2D
10.1
Description
10.2
Properties
10.3
Constraints
10.4
Example
11.
Cropping3D
11.1
Description
11.2
Properties
11.3
Constraints
11.4
Example
12.
UpSampling1D
12.1
Description
12.2
Properties
12.3
Constraints
12.4
Example
13.
UpSampling2D
13.1
Description
13.2
Properties
13.3
Constraints
13.4
Example
14.
UpSampling3D
14.1
Description
14.2
Properties
14.3
Constraints
14.4
Example
파트 IV.
Pooling Layer
1.
MaxPooling1D
1.1
Description
1.2
Properties
1.3
Constraints
1.4
Example
2.
MaxPooling2D
2.1
Format
2.2
Description
2.3
Properties
2.4
Constraints
2.5
Example
3.
Global Average Pooling 2D
3.1
Format
3.2
Description
3.3
Properties
3.4
Constraints
3.5
Example
4.
Average Pooling 2D
4.1
Format
4.2
Description
4.3
Properties
4.4
Constraints
4.5
Example
파트 V.
Application Layer
1.
Inception Res Net V2
1.1
Format
1.2
Description
1.3
Properties
1.4
Constraints
1.5
Example
2.
Inception V3
2.1
Format
2.2
Description
2.3
Properties
2.4
Constraints
2.5
Example
파트 VI.
Recurrent Layer
1.
GRU
1.1
Format
1.2
Description
1.3
Properties
1.4
Constraints
1.5
Example
2.
RNN
2.1
Description
2.2
Properties
2.3
Constraints
2.4
Example
3.
LSTM
3.1
Description
3.2
Properties
3.3
Constraints
3.4
Example
파트 VII.
Advanced Activations Layer
1.
LeakyReLU
1.1
Format
1.2
Description
1.3
Properties
1.4
Constraints
1.5
Example
2.
ELU
2.1
Description
2.2
Properties
2.3
Constraints
2.4
Example
파트 VIII.
Merge Layer
1.
Add
1.1
Description
1.2
Properties
1.3
Constraints
1.4
Example
2.
Concatenate
2.1
Description
2.2
Properties
2.3
Constraints
2.4
Example
파트 IX.
Normalization Layer
1.
Batch Normalizaion
1.1
Description
1.2
Properties
1.3
Constraints
1.4
Example
파트 X.
Embedding Layer
1.
Embedding
1.1
Description
1.2
Properties
1.3
Constraints
1.4
Example
파트 XI.
Applications
1.
VGG16
1.1
Description
1.2
Properties
1.3
Constraints
1.4
Example
2.
ResNet50
2.1
Description
2.2
Properties
2.3
Constraints
2.4
Example
Brightics ML v3.7 Functional _Deep Learning
