neural_networks_class_01.py

#!/usr/bin/python3
# ===================================================================
#
# ===================================================================
# from: Neural Networks from Scratch - P.1 Intro and Neuron Code
#       https://www.youtube.com/watch?v=Wo5dMEP_Bb
# ===================================================================

import sys
import numpy as np
import mathplotlib

print(f'Python     : {sys.verson}')
print(f'Numpy      : (np.__version__}')
print(f'Mathplotlib: {matjplotlib.__version__}')


loss = -np.log(
    np.sum(
        y * np_exp(
            np.dot(
                np.maximum(
                    0,
                    np.dot(
                        np.maximum(
                            0,
                            np.dot(
                                x,
                                w1.T
                             ) + b1
                        ),
                        w2.T        
                    ) + b2,
                ),
                w3.T
            ) + b3
        ) /
        np.sum(
            np.exp(
                np.dot(
                    np.maximum(
                        0,
                        np.dot(
                            np.maximum(
                                0,
                                np.dot(
                                    x,
                                    w1.T
                                ) + b1
                            ),
                            w2.T
                        ) + b2
                    ),
                    w3.T
                ) + b3
            ),
            axis=1,
            keepdims=True
        )
    )
)