Neural Networks from scratch

import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline

def relu(x):
    return np.max(0, x)

X = np.array([[0, 0],
             [0, 1],
             [1, 0],
             [1, 1]])
y = np.array([0, 1, 1, 0])

plt.scatter(X[:, 0], X[:, 1],c=y)

<matplotlib.collections.PathCollection at 0x120334d50>

X.shape

(4, 2)

X

array([[0, 0],
       [0, 1],
       [1, 0],
       [1, 1]])

layers = [2, 1]

B = [np.zeros(n) for n in layers]

W = [None]*len(layers)

W[0] = np.zeros((X.shape[1], layers[0]))

W

[array([[0., 0.],
        [0., 0.]]), None]

for i in range(1, len(layers)):
    W[i] = np.zeros((layers[i-1], layers[i]))

W[1]

array([[0.],
       [0.]])

X.shape, W[0].shape

((4, 2), (2, 2))

X.shape

(4, 2)