06.11_Bonus_Additional_reading_resources.ipynb

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    "## Bonus: Additional reading resources\n",
    "\n",
    "### Weight of Evidence\n",
    "\n",
    "- [WoE Module from StatSoft](http://documentation.statsoft.com/portals/0/formula%20guide/Weight%20of%20Evidence%20Formula%20Guide.pdf)\n",
    "- [WoE Statistica](http://documentation.statsoft.com/StatisticaHelp.aspx?path=WeightofEvidence/WeightofEvidenceWoEIntroductoryOverview)\n",
    "\n",
    "\n",
    "### Score card development for credit risk\n",
    "\n",
    "- [Plug and Score](https://plug-n-score.com/learning/scorecard-development-stages.htm#Binning)\n",
    "- [Score card development from SAS](http://www.sas.com/storefront/aux/en/spcrisks/59376_excerpt.pdf)\n",
    "\n",
    "\n",
    "### Alternative methods of categorical variable encoding\n",
    "\n",
    "- [Will's blog](http://www.willmcginnis.com/2015/11/29/beyond-one-hot-an-exploration-of-categorical-variables/)\n",
    "- [Visiting Categorical Features and Encoding in Decision Trees](https://medium.com/data-design/visiting-categorical-features-and-encoding-in-decision-trees-53400fa65931)\n",
    "- [Feature Engineering: A comprehensive Overview](https://www.trainindata.com/post/feature-engineering-comprehensive-overview)\n",
    "- [Smarter Ways to Encode Categorical Data for Machine Learning](https://towardsdatascience.com/smarter-ways-to-encode-categorical-data-for-machine-learning-part-1-of-3-6dca2f71b159)\n",
    "- [Classification of Tutor systems with high cardinality (KDD competition)](http://pslcdatashop.org/KDDCup/workshop/)\n",
    "- [Light weight solution to KDD data mining challenge](http://pslcdatashop.org/KDDCup/workshop/)\n",
    "\n",
    "### Several encoding and imputation methods described in this course\n",
    "\n",
    "- [The 2009 Knowledge Discovery in Data Competition (KDD Cup 2009)](http://www.mtome.com/Publications/CiML/CiML-v3-book.pdf)"
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