10-CNN

Practice 10 - CNN in TensroFlow

This practice is refer to the following resources credited to Morvan.

• 莫烦PYTHON - TensorFlow: 什么是卷积神经网络 CNN (Convolutional Neural Network)
• 莫烦PYTHON - TensorFlow: CNN 卷积神经网络 1
• 莫烦PYTHON - TensorFlow: CNN 卷积神经网络 2
• 莫烦PYTHON - TensorFlow: CNN 卷积神经网络 3

For more detail about CNN, you can watch the following video on YouTube.

• CNN (Convolutional Neural Network)

  

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Execution

1. Run main.py

   # Make sure your current directory is in this folder
   $ python3 main.py

2. 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)
   Step   0: 0.113
   Step  50: 0.808
   Step 100: 0.866
   Step 150: 0.9
   Step 200: 0.909
   Step 250: 0.927
   Step 300: 0.936
   Step 350: 0.94
   Step 400: 0.95
   Step 450: 0.957
   Step 500: 0.957
   Step 550: 0.963
   Step 600: 0.958
   Step 650: 0.965
   Step 700: 0.961
   Step 750: 0.97
   Step 800: 0.964
   Step 850: 0.965
   Step 900: 0.973
   Step 950: 0.974

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References

• TensorFlow Official - Tutorial
• GitHub - tensorFlow/tensorflow
• 莫烦PYTHON - TensorFlow