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Machine Learning

Probability and Statistics for Machine Learning

Introduction Basics of Data Analysis Probability for Discrete Random Variable Poisson Distribution Chi-Square Distribution P-value and Statistical Hypothesis Power and Sample Size Hypothesis Test Old Hypothesis Test Multi Armed Bandit Bayesian Inference Bayesian Updating with Continuous Priors Discrete Distribution Comparison of Bayesian and frequentist inference Confidence Intervals for Normal Data Frequenist Methods Null Hypothesis Significance Testing Confidence Intervals: Three Views Confidence Intervals for the Mean of Non-normal Data Probabilistic Prediction

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