Session 1 - Generalized Machine Learning.ipynb

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   "source": [
    "# Generalized Machine Learning \n",
    "\n",
    "- A spatial description of the ML problem \n",
    "- The bias/variance trade-off \n",
    "- Model selection and search \n",
    "- Generalized machine learning \n",
    "- Deploying machine learning models"
   ]
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   "source": [
    "%matplotlib inline \n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd \n",
    "import seaborn as sns \n",
    "import matplotlib.pyplot as plt \n",
    "\n",
    "sns.set_context('notebook')\n",
    "sns.set_style('whitegrid')"
   ]
  },
  {
   "cell_type": "markdown",
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   "source": [
    "## The Machine Learning Problem"
   ]
  },
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   },
   "source": [
    "### Learning from Examples"
   ]
  },
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   },
   "source": [
    "### Terminology"
   ]
  },
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   "metadata": {
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   },
   "source": [
    "### Categorized by Input Type"
   ]
  },
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   "metadata": {
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    }
   },
   "source": [
    "### Categorized by Output Type"
   ]
  },
  {
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   "metadata": {
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    }
   },
   "source": [
    "## Regression"
   ]
  },
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   },
   "source": [
    "### Hypothesis"
   ]
  },
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   },
   "source": [
    "### Example"
   ]
  },
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   },
   "source": [
    "### Evaluation"
   ]
  },
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    }
   },
   "source": [
    "## Classification"
   ]
  },
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   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
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    }
   },
   "source": [
    "### Hypothesis"
   ]
  },
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   "cell_type": "markdown",
   "metadata": {
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     "slide_type": "subslide"
    }
   },
   "source": [
    "### Example"
   ]
  },
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   "metadata": {
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     "slide_type": "subslide"
    }
   },
   "source": [
    "### Evaluation"
   ]
  },
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   },
   "source": [
    "## Clustering"
   ]
  },
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   "metadata": {
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    }
   },
   "source": [
    "### Hypothesis"
   ]
  },
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   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Example"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Evaluation"
   ]
  },
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   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Generalized Machine Learning"
   ]
  },
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   "metadata": {
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   },
   "source": [
    "### Features"
   ]
  },
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   },
   "source": [
    "### Models"
   ]
  },
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   },
   "source": [
    "### Parameters and Hyperparameters"
   ]
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   },
   "source": [
    "## Machine Learning API"
   ]
  },
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   },
   "source": [
    "### Estimators"
   ]
  },
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   },
   "source": [
    "### Models"
   ]
  },
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   },
   "source": [
    "### Transformers"
   ]
  },
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   },
   "source": [
    "### Pipelines"
   ]
  },
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   "metadata": {
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    }
   },
   "source": [
    "## Model Selection"
   ]
  },
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   "cell_type": "markdown",
   "metadata": {
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     "slide_type": "subslide"
    }
   },
   "source": [
    "### Model Selection Triple"
   ]
  },
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   "metadata": {
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   },
   "source": [
    "### A Search Problem"
   ]
  },
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   "metadata": {
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    }
   },
   "source": [
    "### Visual Steering"
   ]
  },
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   },
   "source": [
    "## Complexity"
   ]
  },
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   "metadata": {
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    }
   },
   "source": [
    "### Underfitting"
   ]
  },
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   "metadata": {
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    }
   },
   "source": [
    "### Overfitting"
   ]
  },
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    }
   },
   "source": [
    "### Cross-Validation"
   ]
  },
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   "metadata": {
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   },
   "source": [
    "### Bias and Variance"
   ]
  },
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   },
   "source": [
    "### Sources of Complexity"
   ]
  },
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   "metadata": {
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    }
   },
   "source": [
    "### Interpretability"
   ]
  },
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   },
   "source": [
    "## Deployment"
   ]
  },
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   "metadata": {
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    }
   },
   "source": [
    "### Classification/Regression Workflow"
   ]
  },
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   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
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    }
   },
   "source": [
    "### Clustering Workflow"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
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    }
   },
   "source": [
    "### Data Product Pipeline"
   ]
  }
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