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1. cross-validation-glm-vs-lmer-vs-brms cross-validation-glm-vs-lmer-vs-brms Public

   Repeated k-fold cross validation to evaluate glm (linear) versus lmer (mixed) versus brms (bayesian) models

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2. baseball-heat-map baseball-heat-map Public

   Use baseball data from Mike Trout to model exit velocity as a function of pitch location. Visualize with a heat map in R

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3. keras-logistic-regression keras-logistic-regression Public

   Show how a Keras neural network simplifies to a logistic regression

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4. neural-network-regularization neural-network-regularization Public

   Use Keras in R to purposefully overfit the MNIST dataset. Then improve generalizability with dropout and regularization

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5. accuracy-sensitivity-specificity-precision accuracy-sensitivity-specificity-precision Public

   Unbalanced targets require special attention to the sensitivity vs specificity tradeoff, and the sensitivity vs precision tradeoff. Here I use two examples, cancer and loan defaults, to demonstrate…

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6. feature-selection-4ways feature-selection-4ways Public

   Do variable selection in 4 different ways: 1) rank models by AICc, 2) leave one out or k-fold cross validation, 3) Bayesian variable selection, and 4) use caret's recursive feature elimination.

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