GitHub - pawel-zajac-dev/Bayesian-Reinforcement-Machine-Learning-Statistics: This project explores data analysis, blending core Probability Theory and Descriptive Statistics with Statistical Inference and Bayesian Machine Learning (Regression/Classification). It concludes with a comparative study of Frequentist vs. Bayesian A/B Testing.

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Name		Name	Last commit message	Last commit date
Latest commit History 44 Commits
1.1 CDFs & Percentiles.ipynb		1.1 CDFs & Percentiles.ipynb
1.2 Confidence Intervals z-statistic vs t-statistic .ipynb		1.2 Confidence Intervals z-statistic vs t-statistic .ipynb
1.3 Hypothesis Testing z-test.ipynb		1.3 Hypothesis Testing z-test.ipynb
1.4 Chi-Square Goodness of Fit Test.ipynb		1.4 Chi-Square Goodness of Fit Test.ipynb
2.1 Epsilon Greedy Reinforcement.ipynb		2.1 Epsilon Greedy Reinforcement.ipynb
2.2 Comparing Different Epsilons & Bernoulli.ipynb		2.2 Comparing Different Epsilons & Bernoulli.ipynb
2.3 Initial Optimistic Values Reinforcement.ipynb		2.3 Initial Optimistic Values Reinforcement.ipynb
2.4 UCB1 Reinforcement.ipynb		2.4 UCB1 Reinforcement.ipynb
2.5 Bernoulli Thompson Sampling (Bayesian) Reinforcement.ipynb		2.5 Bernoulli Thompson Sampling (Bayesian) Reinforcement.ipynb
2.6 Gaussian Thompson Sampling (Bayesian) Reinforcement.ipynb		2.6 Gaussian Thompson Sampling (Bayesian) Reinforcement.ipynb
3.1 Bayesian Linear Regression.ipynb		3.1 Bayesian Linear Regression.ipynb
advertisement_clicks.csv		advertisement_clicks.csv
advertising.csv		advertising.csv
titanic_train.csv		titanic_train.csv
weight.csv		weight.csv

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This project explores data analysis, blending core Probability Theory and Descriptive Statistics with Statistical Inference and Bayesian Machine Learning (Regression/Classification). It concludes with a comparative study of Frequentist vs. Bayesian A/B Testing.