step 1:-importing the MobileNet pretrained model and download the weight of mobileNet.
step 2:-next we are making our layer that will be implmenting on top of the Mobilenet layer.
step 3:-next we are importing the necessary layers and num_classes here is the category in total,which we are predicting. means how many different catagory we are predicting here i am predicting two values.
step 4:-next we are doing some image augmentation,generally we do not have the lots of images so by the augmentation we just make new images like by doing zoom,tilt the image etc . a little change in the image for system it is pure new image. here also defining the data location of training and testing or validation dataset. the location in which your data set is present provide the location here.
step 5:-next we are setting up the epochs , optimizers like RMSprop also saving the model,,in each epochs accuracy is mention the best accuracy will be saved.
step 6:-here we are fitting the model ans also defining the running accuracy between testing and validation/testing dataset.
step 7:-next we are simply checking our model that it is predicting right or not.
