import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
a = np.linspace(-10, 10, 100)
b = 1/(1 + np.exp(-a))
plt.fashion.use("seaborn-v0_8-dark")
plt.plot(a,b,lw=4,marker="*",coloration="purple",markersize=10,markerfacecolor="purple")
plt.xlabel("a",fontsize=12,coloration="blue")
plt.ylabel("Sigmoid(A)",fontsize=12,coloration="blue")
plt.title("Sigmoid Functionn",fontsize=15,coloration="blue")
plt.present()
def sig(x):return 1/(1 + np.exp(-x))
y = 1.0
print("Worth is %.2f"%sig(y))
Worth is 0.73
m = -1.0
print("Worth is %.2f"%sig(m))
Worth is 0.27
n = -0.00478
print("Worth is %.2f"%sig(n))
Worth is 0.50
