notebooks/Chapter_01-Introduction.ipynb

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    "# Chapter 1 - Introduction\n",
    "\n",
    "\n",
    "## 1.1 - Example: Polynomial Curve Fitting\n",
    "\n",
    "## 1.2 - Probability Theory\n",
    "\n",
    "### 1.2.1 - Probability densities\n",
    "### 1.2.2 - Expectations and covariances\n",
    "### 1.2.3 - Bayesian probabilities\n",
    "### 1.2.4 - The Gaussian distribution\n",
    "### 1.2.5 - Curve fitting re-visited\n",
    "### 1.2.6 - Bayesian curve fitting\n",
    "\n",
    "## 1.3 - Model Selection\n",
    "## 1.4 - The Curse of Dimensionality\n",
    "## 1.5 - Decision Theory\n",
    "\n",
    "### 1.5.1 - Minimizing the misclassification rate\n",
    "### 1.5.2 - Minimizing the expected loss\n",
    "### 1.5.3 - The reject option\n",
    "### 1.5.4 - Inference and decision\n",
    "### 1.5.5 - Loss functions for regression\n",
    "\n",
    "## 1.6 - Information Theory\n",
    "\n",
    "### 1.6.1 - Relative entropy an mutual information"
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    "# TODO: Explanations and code examples"
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