CS231n Softmax (Cross-entropy loss) - Vectorized

softmax.py

import numpy as np

W = np.array([(0.01,-0.05,0.1,0.05),(0.7,0.2,0.05,0.16),(0.0,-0.45,-0.2, 0.03)]) #Weights
xi = np.array([-15,22,-44,56]) #Input
b = np.array([0.0,0.2,-0.3]) #Bias

delta = 1

y = np.sum((np.dot(W,xi),b), axis=0)

p = np.exp(y)/np.sum(np.exp(y))

final = -np.log(p[p.size-1])

# final = 1.0401905694301092