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edenau/NumPy-linear_reg-2.py

Last active December 27, 2019 16:39
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NumPy-linear_reg-2.py
# Make sure X and y are linearly correlated with normally distributed noise
n = 10000 # 10000 datum points
X = np.random.uniform(-10,10, n)
noise = np.random.normal(0, 3, n) # Gaussian distribution
true_w, true_b = 7.6, -3.3
y = true_w * X + true_b + noise # y = w * x + b + ε
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