Original article was published on Deep Learning on Medium

Neural Network Steps

Single or multiple training examples.

- Define neural network structure
- Define parameter(w, b)or initialize
- For loop

1)define forward propagation

2) compute cost function

3)define backward propagation

4)update parameters using Gradient descent.

Do until minimize the cost function

After all

If y^ is less than 0.5 then output is zero

Else

Y^ is greater than 0.5 then output is 1

In the neural network use single training example loss function =1/2(y-y^)

And cost function for multiple training example

L(y,y^)=1/m(y.log(y^[i])-(y-1).log (y^[i]-1)

In the hidden layer use tanh() activation function and output layer use sigmoid activation function .

In the backward propagation calculate the derivative function….

#machine learning#data science

#neurak