Dlearning

Deep Learning

Basic

• 神经网络：

algorithm1

input1

output

input2

input3

input4

algorithm2

• 监督学习：1个x对应1个y；

• Sigmoid:
  $$sigmoid=\frac{1}{1+e^{-x}}$$

• ReLU :线性整流函数；

Logistic Regression

–>binary classification / x–>y 0 1

some sign

$$\begin{gathered} (x,y),x\in R^{n_x},y\in 0,1 \\ M=m_{train}{m}_{test}=test \\ M:(x^{(1)},y^{(1)}),(x^{(2)},y^{(2)})...,(x^{(m)},y^{(m)}) \\ X=\left[\begin{array}{cccc}{x}^{(1)}& x^{(2)}& \cdots & x^{(m)}\end{array}\right]\leftarrow n^x\times m\text{\hspace{1em}(3)} \end{gathered}$$