notebooks/Chapter_06-Kernel_Methods.ipynb

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    "# Chapter 6 - Kernel Methods\n",
    "\n",
    "## 6.1 - Dual Representations\n",
    "## 6.2 - Constructing Kernels\n",
    "## 6.3 - Radial Basis Function Networks\n",
    "\n",
    "### 6.3.1 - Nadaraya-Watson model\n",
    "\n",
    "## 6.4 - Gaussian Processes\n",
    "\n",
    "### 6.4.1 - Linear regression revisited\n",
    "### 6.4.2 - Gaussian processes for regression\n",
    "### 6.4.3 - Learning the hyperparameters\n",
    "### 6.4.4 - Automatic relevance determination\n",
    "### 6.4.5 - Gaussian processes for classification\n",
    "### 6.4.6 - Laplace approximation\n",
    "### 6.4.7 - Connection to neural networks"
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