Session 3 - Clustering and Similarity.ipynb

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   "source": [
    "# Clustering and Similarity"
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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')"
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   "source": [
    "## Distance and Similarity"
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   "source": [
    "### Minkowski Distance "
   ]
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   "source": [
    "### Mahalanobis Distance "
   ]
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   "source": [
    "### Cosine Distance "
   ]
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   "source": [
    "### Other Distance Metrics"
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   "source": [
    "## Clustering Metrics"
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   "source": [
    "### Silhouette Scores"
   ]
  },
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   },
   "source": [
    "### Inter-Cluster Distance Maps"
   ]
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   },
   "source": [
    "### Rand Index"
   ]
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   },
   "source": [
    "## Agglomerative Clustering"
   ]
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   },
   "source": [
    "## Partitive Clustering"
   ]
  },
  {
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   "metadata": {
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   },
   "source": [
    "## Curse of Dimensionality"
   ]
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   },
   "source": [
    "### No Free Lunch"
   ]
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