Dynamic mini batch creation during training 

One of the ways to only load the data corresponding to a mini-batch is to dynamically create mini-batches by processing images randomly from their location. The number of images to be processed in a mini-batch would be equal to the mini-batch size we specify. Of course there would be some bottleneck in the training process because of the dynamic mini-batch creation during training time but that bottleneck is negligible. Specially packages such as keras have efficient dynamic batch creation mechanism. We would be leveraging flow_from_directory functionality in keras to dynamically create mini-batches during training to reduce the memory requirements of the training process. We will still continue ...

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