Implemetation of a 2-layered shallow neural network on the cat-vs-non-cat dataset. The input images are (64,64,3) dimensioned which are flattened to (12288,1) dimensioned vector per training image before feeding into the model.
Note: The source_code file two_layered_img_classification.py imports a helper_functions module in the beggining which contains some helper functions like sigmoid() function, load_data() function, initialize_parameters() function etc. This module can be accessed at helper_functions.py file.