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    "# 多层感知机\n",
    ":label:`chap_perceptrons`\n",
    "\n",
    "在本章中，我们将第一次介绍真正的*深度*网络。\n",
    "最简单的深度网络称为*多层感知机*。多层感知机由多层神经元组成，\n",
    "每一层与它的上一层相连，从中接收输入；\n",
    "同时每一层也与它的下一层相连，影响当前层的神经元。\n",
    "当我们训练容量较大的模型时，我们面临着*过拟合*的风险。\n",
    "因此，本章将从基本的概念介绍开始讲起，包括*过拟合*、*欠拟合*和模型选择。\n",
    "为了解决这些问题，本章将介绍*权重衰减*和*暂退法*等正则化技术。\n",
    "我们还将讨论数值稳定性和参数初始化相关的问题，\n",
    "这些问题是成功训练深度网络的关键。\n",
    "在本章的最后，我们将把所介绍的内容应用到一个真实的案例：房价预测。\n",
    "关于模型计算性能、可伸缩性和效率相关的问题，我们将放在后面的章节中讨论。\n",
    "\n",
    ":begin_tab:toc\n",
    " - [mlp](mlp.ipynb)\n",
    " - [mlp-scratch](mlp-scratch.ipynb)\n",
    " - [mlp-concise](mlp-concise.ipynb)\n",
    " - [underfit-overfit](underfit-overfit.ipynb)\n",
    " - [weight-decay](weight-decay.ipynb)\n",
    " - [dropout](dropout.ipynb)\n",
    " - [backprop](backprop.ipynb)\n",
    " - [numerical-stability-and-init](numerical-stability-and-init.ipynb)\n",
    " - [environment](environment.ipynb)\n",
    " - [kaggle-house-price](kaggle-house-price.ipynb)\n",
    ":end_tab:\n"
   ]
  }
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