I have tried to implement a generic FFNN for a simple multi-class classification problem in similar lines to
" vectorization of weights & inputs "
- I found the loss function vary drastically each time I run the “fit function of the generic class”. Why is this happening ?
- I would like to know if conceptually the implementation is correct?
Your feedback would be helpful in correcting my mistakes.
Link for the my code : https://github.com/abhiramangit/Imag_reco/blob/master/Generic_FFNN_Class.ipynb