This practice is refer to the following resources credited to Morvan.
- Run
main1.py# Make sure your current directory is in this folder $ python3 main1.py - If succeed, you will get the following result (take few minutes)
# If you run the program first time, you may download the datasets first (optional) Downloading data from https://s3.amazonaws.com/img-datasets/mnist.npz 11493376/11490434 [==============================] - 12s 1us/step # If you have already run the pregram before, you may see the following information (optional) Extracting MNIST_data/train-images-idx3-ubyte.gz Extracting MNIST_data/train-labels-idx1-ubyte.gz Extracting MNIST_data/t10k-images-idx3-ubyte.gz Extracting MNIST_data/t10k-labels-idx1-ubyte.gz # The probability of prediction (the result is not unique) Epoch 1: Loss = 0.070371628 Epoch 2: Loss = 0.061792824 Epoch 3: Loss = 0.057367947 Epoch 4: Loss = 0.055086661 Epoch 5: Loss = 0.050911840 Epoch 6: Loss = 0.049793467 Epoch 7: Loss = 0.049022138 Epoch 8: Loss = 0.047246918 Epoch 9: Loss = 0.045892879 Epoch 10: Loss = 0.045229465 Epoch 11: Loss = 0.044753738 Epoch 12: Loss = 0.041483913 Epoch 13: Loss = 0.043634389 Epoch 14: Loss = 0.042594045 Epoch 15: Loss = 0.044084344 Epoch 16: Loss = 0.042420749 Epoch 17: Loss = 0.042780302 Epoch 18: Loss = 0.042752471 Epoch 19: Loss = 0.041828986 Epoch 20: Loss = 0.040571641
- You will get the following result (the result is not unique)
- Run
main2.py# Make sure your current directory is in this folder $ python3 main2.py - If succeed, you will get the following result (take few minutes)
# If you run the program first time, you may download the datasets first (optional) Downloading data from https://s3.amazonaws.com/img-datasets/mnist.npz 11493376/11490434 [==============================] - 12s 1us/step # If you have already run the pregram before, you may see the following information (optional) Extracting MNIST_data/train-images-idx3-ubyte.gz Extracting MNIST_data/train-labels-idx1-ubyte.gz Extracting MNIST_data/t10k-images-idx3-ubyte.gz Extracting MNIST_data/t10k-labels-idx1-ubyte.gz # The probability of prediction (the result is not unique) Epoch 1: Loss = 0.070924804 Epoch 2: Loss = 0.059744425 Epoch 3: Loss = 0.057972237 Epoch 4: Loss = 0.049820133 Epoch 5: Loss = 0.049503040 Epoch 6: Loss = 0.048985694 Epoch 7: Loss = 0.046035368 Epoch 8: Loss = 0.045065016 Epoch 9: Loss = 0.046500780 Epoch 10: Loss = 0.041021083 Epoch 11: Loss = 0.042688243 Epoch 12: Loss = 0.042602878 Epoch 13: Loss = 0.043667346 Epoch 14: Loss = 0.042277016 Epoch 15: Loss = 0.042719189 Epoch 16: Loss = 0.040399708 Epoch 17: Loss = 0.039351098 Epoch 18: Loss = 0.039856773 Epoch 19: Loss = 0.040220011 Epoch 20: Loss = 0.040195532
- You will get the following result (the result is not unique)
