Neural Networks from scratch – Nipun Batra Blog

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

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

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

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

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X.shape

(4, 2)

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

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layers = [2, 1]

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

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W = [None]*len(layers)

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

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

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

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W[1]

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

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X.shape, W[0].shape

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

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X.shape

(4, 2)