A developing collection of experiments in Statistics, Game Theory and Probability.
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Regret Matching - An introduction to the strategy-finding method of regret matching. Mathematical analysis, probabilities and simulation.
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Linear Regression: Simulation and Calculation - Optimising Linear Regression via Simulated Annealing. Comparison with standard statistical regression calculations (Normal Equations).
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Classification - In or Out? - Performing Logistic Regression from first principles via Gradient Ascent. Plotting of Decision Boundary and Training/Testing models.
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Function Approximation - Outlining one Universal Approximation Theorem, writing a neural network from scratch and comparing models for a parabola. Debugging Neural Networks.