diff --git a/11_training_deep_neural_networks.ipynb b/11_training_deep_neural_networks.ipynb
index 26ab2d5fc..470e5dc4f 100644
--- a/11_training_deep_neural_networks.ipynb
+++ b/11_training_deep_neural_networks.ipynb
@@ -1,4830 +1,5843 @@
{
- "cells": [
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "**11장 – 심층 신경망 훈련하기**"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "_이 노트북은 11장에 있는 모든 샘플 코드와 연습문제 해답을 가지고 있습니다._"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "
"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# 설정"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "먼저 몇 개의 모듈을 임포트합니다. 맷플롯립 그래프를 인라인으로 출력하도록 만들고 그림을 저장하는 함수를 준비합니다. 또한 파이썬 버전이 3.5 이상인지 확인합니다(파이썬 2.x에서도 동작하지만 곧 지원이 중단되므로 파이썬 3을 사용하는 것이 좋습니다). 사이킷런 버전이 0.20 이상인지와 텐서플로 버전이 2.0 이상인지 확인합니다."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 1,
- "metadata": {},
- "outputs": [],
- "source": [
- "# 파이썬 ≥3.5 필수\n",
- "import sys\n",
- "assert sys.version_info >= (3, 5)\n",
- "\n",
- "# 사이킷런 ≥0.20 필수\n",
- "import sklearn\n",
- "assert sklearn.__version__ >= \"0.20\"\n",
- "\n",
- "# 텐서플로 ≥2.0 필수\n",
- "import tensorflow as tf\n",
- "from tensorflow import keras\n",
- "assert tf.__version__ >= \"2.0\"\n",
- "\n",
- "%load_ext tensorboard\n",
- "\n",
- "# 공통 모듈 임포트\n",
- "import numpy as np\n",
- "import os\n",
- "\n",
- "# 노트북 실행 결과를 동일하게 유지하기 위해\n",
- "np.random.seed(42)\n",
- "\n",
- "# 깔끔한 그래프 출력을 위해\n",
- "%matplotlib inline\n",
- "import matplotlib as mpl\n",
- "import matplotlib.pyplot as plt\n",
- "mpl.rc('axes', labelsize=14)\n",
- "mpl.rc('xtick', labelsize=12)\n",
- "mpl.rc('ytick', labelsize=12)\n",
- "\n",
- "# 그림을 저장할 위치\n",
- "PROJECT_ROOT_DIR = \".\"\n",
- "CHAPTER_ID = \"deep\"\n",
- "IMAGES_PATH = os.path.join(PROJECT_ROOT_DIR, \"images\", CHAPTER_ID)\n",
- "os.makedirs(IMAGES_PATH, exist_ok=True)\n",
- "\n",
- "def save_fig(fig_id, tight_layout=True, fig_extension=\"png\", resolution=300):\n",
- " path = os.path.join(IMAGES_PATH, fig_id + \".\" + fig_extension)\n",
- " print(\"그림 저장:\", fig_id)\n",
- " if tight_layout:\n",
- " plt.tight_layout()\n",
- " plt.savefig(path, format=fig_extension, dpi=resolution)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# 그레이디언트 소실과 폭주 문제"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 2,
- "metadata": {},
- "outputs": [],
- "source": [
- "def logit(z):\n",
- " return 1 / (1 + np.exp(-z))"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "그림 저장: sigmoid_saturation_plot\n"
- ]
- },
- {
- "data": {
- "image/png": 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\n",
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