12424 Repositories
dsc-2-23-03-kolmogorov-smirnov-test
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dsc-2-23-02-distributions-recap
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dsc-2-23-01-introduction
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dsc-2-22-16-section-recap
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dsc-2-22-15-optimality-of-naive-bayes
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dsc-2-22-14-document-classification-using-naive-bayes-lab
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dsc-2-22-13-text-classification
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dsc-2-22-12-naive-bayes-and-nlp-in-sklearn
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dsc-2-22-11-natural-language-processing-lab
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dsc-2-22-10-natural-language-processing
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dsc-2-22-08-NB-sklearn
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dsc-2-22-07-NB-Numpy-Lab
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dsc-2-22-06-naive-bayes-assumptions
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dsc-2-22-05-MAP-naive-bayes
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dsc-2-22-03-MLE-gaussian-lab
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dsc-2-22-03-MLE-Gaussian
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dsc-2-22-01-introduction
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dsc-2-21-16-section-recap
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dsc-2-21-15-frequentist-bayesian-essay
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dsc-2-21-14-bayesian-frameowork-lab
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dsc-2-21-13-conjugate-prior
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dsc-2-21-12-PE-MAP
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dsc-2-21-11-PE-MLE
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dsc-2-21-10-monty-hall-lab
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dsc-2-21-09-bayes-theorem-lab
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dsc-2-21-08-bayes-theorem
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dsc-2-21-07-probability-simulations
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dsc-2-21-06-total-prob-law-lab
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dsc-2-21-05-total-prob-law
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dsc-2-21-04-conditional-prob-lab
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dsc-2-21-03-conditional-prob
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dsc-2-21-01-introduction
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dsc-2-20-20-anova-lab
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dsc-2-20-19-anova
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dsc-2-20-18-section-recap
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dsc-2-20-18-goodhearts-law-and-metric-tracking
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dsc-2-20-17-ab-testing-lab
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dsc-2-20-16-ab-testing
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dsc-2-20-15-multiple-comparisons-problem
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dsc-2-20-13-statistical-power-lab
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dsc-2-20-12-statistical-power
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dsc-2-20-11type-1-and-type-2-errors-lab
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dsc-2-20-10-type-1-and-type-2-errors
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dsc-2-20-09-2-sample-t-tests-lab
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dsc-2-20-07-calculating-p-using-binomial-distribution
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dsc-2-20-06-effect-sizes-lab
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dsc-2-20-05-effect-sizes
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dsc-2-20-04-p-values-and-null-hypothesis
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dsc-2-20-03-introduction-to-experimental-design
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dsc-2-20-01-introduction
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