This is an abstract preview of a saved artificial neural network for SymfonyCon Madrid 2014

ann_guts

neurons (num_inputs, activation_function, activation_steepness)=(0, 0, 0.00000000000000000000e+00) (0, 0, 0.00000000000000000000e+00) (0, 0, 0.00000000000000000000e+00) (0, 0, 0.00000000000000000000e+00) (0, 0, 0.00000000000000000000e+00) (0, 0, 0.00000000000000000000e+00) (0, 0, 0.00000000000000000000e+00) (0, 0, 0.00000000000000000000e+00) (0, 0, 0.00000000000000000000e+00) (0, 0, 0.00000000000000000000e+00) (10, 5, 5.00000000000000000000e-01) (10, 5, 5.00000000000000000000e-01) (10, 5, 5.00000000000000000000e-01) (0, 5, 0.00000000000000000000e+00) (4, 5, 5.00000000000000000000e-01) (4, 5, 5.00000000000000000000e-01) (4, 5, 5.00000000000000000000e-01) (4, 5, 5.00000000000000000000e-01) (4, 5, 5.00000000000000000000e-01) (4, 5, 5.00000000000000000000e-01) (4, 5, 5.00000000000000000000e-01) (4, 5, 5.00000000000000000000e-01) (4, 5, 5.00000000000000000000e-01) (0, 5, 0.00000000000000000000e+00) 
connections (connected_to_neuron, weight)=(0, 2.74120140075683593750e+00) (1, 1.17843687534332275391e+00) (2, 6.52682423591613769531e-01) (3, 1.62521958351135253906e+00) (4, -4.13283109664916992188e+00) (5, 6.68983578681945800781e-01) (6, 2.90351939201354980469e+00) (7, 1.54306614398956298828e+00) (8, 4.86784726381301879883e-01) (9, -1.27116775512695312500e+00) (0, -7.29453611373901367188e+00) (1, 1.63006329536437988281e+00) (2, 1.52627396583557128906e+00) (3, 1.32863020896911621094e+00) (4, 3.47751951217651367188e+00) (5, 6.00164771080017089844e-01) (6, 9.62386786937713623047e-01) (7, -1.04133701324462890625e+00) (8, 4.00049656629562377930e-01) (9, -1.80864405632019042969e+00) (0, -2.16505870223045349121e-01) (1, 7.43983626365661621094e-01) (2, 1.63793325424194335938e+00) (3, -4.18614834547042846680e-01) (4, -3.44087672233581542969e+00) (5, -2.72563874721527099609e-01) (6, 6.69832277297973632812e+00) (7, -5.78566968441009521484e-01) (8, -4.54963237047195434570e-01) (9, 2.92966723442077636719e+00) (10, -2.62807548046112060547e-01) (11, -1.28047907352447509766e+00) (12, -1.34247377514839172363e-01) (13, -9.85080361366271972656e-01) (10, 4.65072423219680786133e-01) (11, 3.39287161827087402344e-01) (12, -2.78555244207382202148e-01) (13, -9.17742252349853515625e-02) (10, 3.71352076530456542969e-01) (11, 2.53831148147583007812e-01) (12, -3.06476466357707977295e-02) (13, -1.28473326563835144043e-01) (10, 6.97892189025878906250e-01) (11, 4.43554818630218505859e-01) (12, -5.29893994331359863281e-01) (13, 8.20369496941566467285e-02) (10, -2.86632776260375976562e+00) (11, -1.06006765365600585938e+00) (12, 1.15320265293121337891e+00) (13, -2.29793691635131835938e+00) (10, 3.18927526473999023438e-01) (11, 1.34147927165031433105e-01) (12, -2.30030238628387451172e-01) (13, -1.31280690431594848633e-01) (10, -5.61175346374511718750e-01) (11, 1.21003799140453338623e-01) (12, 1.32298707962036132812e+00) (13, -1.28568077087402343750e+00) (10, 3.89801710844039916992e-01) (11, 8.54921713471412658691e-02) (12, -3.57097923755645751953e-01) (13, -1.65683776140213012695e-01) (10, 9.04448449611663818359e-01) (11, 6.77048504352569580078e-01) (12, -7.50013589859008789062e-01) (13, 6.66252374649047851562e-02)