Day092_CNN_theory.ipynb

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    "請閱讀以下文獻，理解 CNN 原理後回答問題\n",
    "- [卷積神經網路原理 - 中文](https://brohrer.mcknote.com/zh-Hant/how_machine_learning_works/how_convolutional_neural_networks_work.html)\n",
    "- [CNN for beginner’s guide](https://adeshpande3.github.io/A-Beginner%27s-Guide-To-Understanding-Convolutional-Neural-Networks/)\n",
    "\n",
    "1. 若使用總共 128 個濾波器 (filters)，對一張 256x256 的影像做完卷積後，共會得到幾張特徵圖 (feature maps)？\n",
    "2. 卷積神經網路中，濾波器的大小 (3x3 or 5x5) 與內部數字的值 (value) 是怎麼決定的呢？\n"
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