Collection of hands-on projects exploring core machine learning and statistics. This series features from-scratch implementations of algorithms for Hypothesis Testing (A/B, Bayesian), Supervised, Unsupervised and Reinforcement Learning.
data-science machine-learning reinforcement-learning svm scikit-learn q-learning regression bayesian-methods supervised-learning classification gaussian-mixture-models sarsa ab-testing trees unsupervised-learning hypothesis-testing monte-carlo-methods a-star-search markov-decision-process expectimax-algorithm
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Updated
Jun 18, 2026 - Python