One epoch update of perceptron weights

perceptron-update-weights-one-epoch.py

weights = initialize_weights(train_data.shape[1])
sum_of_squared_errors = 0.0
for sample in range(train_data.shape[0]):
    vector = train_data.loc[sample].values
    label = train_label.loc[sample]
    prediction = predict(vector, weights, 'step')
    error = label - prediction
    sum_of_squared_errors += error**2
    weights = weights + error * vector
print(f'SSE: {sum_of_squared_errors}')
print(f'Weights: {weights}')