AI/ML Foundations and Applications

From perceptrons to transformers — history, theory, and R implementations of AI and ML.
TUTORIALS

AI/ML Foundations and Applications

From perceptrons to transformers — history, theory, and R implementations of AI and ML.

Generative adversarial networks as minimax games

ai-ml-foundations-and-applications
gans
minimax
zero-sum

Frame GANs as two-player zero-sum games in R, implement a simple GAN training loop for 1D data, visualise the generator-discriminator dynamics, and connect the equilibrium to Nash equilibrium theory.

May 8, 2026

Automated Mechanism Design for Optimal Auctions

ai-ml-foundations-and-applications
mechanism-design
auctions

Training a data-driven auction mechanism using gradient-free optimisation in pure R — learning payment rules from bidder profiles, enforcing incentive compatibility and individual rationality, and benchmarking against Myerson’s optimal auction.

May 8, 2026

Multi-armed bandits and the exploration-exploitation trade-off

ai-ml-foundations-and-applications
multi-armed-bandits
reinforcement-learning
exploration-exploitation

Implementation and analysis of bandit algorithms including epsilon-greedy, UCB1, and Thompson sampling, framed as single-agent games against nature with regret analysis, Bayesian updating, and interactive performance comparisons.

May 8, 2026

From Perceptron to deep learning — a historical R implementation

ai-ml-foundations-and-applications
neural-networks
perceptron
deep-learning
historical

Trace the evolution of neural networks from Rosenblatt’s 1958 Perceptron through the Minsky-Papert critique to backpropagation and modern deep learning, implementing key milestones in R.

May 8, 2026

SHAP Values as Shapley Values — Cooperative Game Theory Meets Explainable AI

ai-ml-foundations-and-applications
shap
shapley-value

Demonstrate that SHAP (SHapley Additive exPlanations) is a direct application of the Shapley value from cooperative game theory, computing exact Shapley values for a 4-feature prediction model by enumerating all coalitions and verifying the efficiency, symmetry, dummy, and additivity axioms in R.

May 8, 2026
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