```python
import numpy as np
from sympy import *
init_printing(use_unicode=True) # 輸出數學格式
import matplotlib.pylab as plt
%matplotlib
```

    Using matplotlib backend: Qt5Agg



```python
M = MatrixSymbol('M', 3, 3)
```


```python
Matrix(M)
```




$$\left[\begin{array}{ccc}M_{0, 0} & M_{0, 1} & M_{0, 2}\\M_{1, 0} & M_{1, 1} & M_{1, 2}\\M_{2, 0} & M_{2, 1} & M_{2, 2}\end{array}\right]$$




```python
x1, x2 = symbols('x1, x2')
w111, w112, w121, w122 = symbols('w111, w121, w112, w122')
w211, w212, w221, w222 = symbols('w211, w221, w212, w222')
b11, b12, b21, b22 = symbols('b11, b12, b21, b22')
X = Matrix([x1, x2]).T
W1 = Matrix([[w111, w121], [w112, w122]])
W2 = Matrix([[w211, w221], [w212, w222]])
B1 = Matrix([b11, b12]).T
B2 = Matrix([b21, b22]).T
```


```python
X * W1 + B1
```




$$\left[\begin{matrix}b_{11} + w_{111} x_{1} + w_{121} x_{2} & b_{12} + w_{112} x_{1} + w_{122} x_{2}\end{matrix}\right]$$




```python
(((X * W1) + B1) * W2) + B2
```




$$\left[\begin{matrix}b_{21} + w_{211} \left(b_{11} + w_{111} x_{1} + w_{121} x_{2}\right) + w_{221} \left(b_{12} + w_{112} x_{1} + w_{122} x_{2}\right) & b_{22} + w_{212} \left(b_{11} + w_{111} x_{1} + w_{121} x_{2}\right) + w_{222} \left(b_{12} + w_{112} x_{1} + w_{122} x_{2}\right)\end{matrix}\right]$$



139fdeeacc2a3cb8cbaafdb3799b6e93fceb06be
ipynb
Jupyter Notebook
DL/Neural Network.ipynb
sppool/works
2ab9c10d7326e0e836f3214f5067b6f070deb2e0
MIT
2020-05-27T16:41:42.000Z
2020-05-27T16:41:42.000Z
DL/Neural Network.ipynb
sppool/works
2ab9c10d7326e0e836f3214f5067b6f070deb2e0
MIT
DL/Neural Network.ipynb
sppool/works
2ab9c10d7326e0e836f3214f5067b6f070deb2e0
MIT
2020-04-11T08:13:29.000Z
2020-05-11T14:15:53.000Z
Qwen/Qwen-72B
1. YES
2. YES