Deep Learning with Spark and TensorFlow
I have a question about neural networks.Say, you are training a NN to recognize handwritten characters 0 and 1, and you have 1000 training images for each character (so 2000 images in total). All images are bitmaps with 0 for black and 1 for white.Now, by accident, all the "0" training-images have an even number of black pixels, and all the "1" training-images have an odd number of black pixels.How do you know that the NN really learns to recognize 0's and 1's, as opposed to recognizing whether the number of pixels in an image is even or odd?