Bitcoin and Cryptocurrency Technologies (a Princeton course on Coursera)
- Scrooge Coin: An implementation of a simple cryptocurrency ledger that allows checking the validity of transactions and thereby processes valid transactions. In particular, it handles the double-spending problem
Neural Networks and Deep Learning (taught by Andrew Ng)
- cat_recognition: A simple Neural Network model using logistic regression to recognize cat images
- planar_data_classification: A one-hidden-layer Neural Network model for learning the leaf patterns of the flower
- building_neural_network_step_by_step: Develop an intuition of the over all structure of a neural network
- cat_recognition_deep: A deep Neural Network model using linear function and ReLU/sigmoid activation functions to recognize cat images
Derivatives (AFM 322 @ University of Waterloo)
- futures: Mechanics of Futures market, Contango vs Backwardation, Cost of Carry, Margin Call
- hedging_using_futures: Long/Short Hedge, Basis, Cross Hedging, Optimal Hedge Ratio, Stack and Roll
- black_scholes: Risk Neutral Valuation, Pricing Formula, Implied Volatility
Artificial Intelligence (CS 486 @ University of Waterloo)
- problem_solving: methodology, heuristics, A* search, CSP, consistency algorithms, backtracking search, local search
- bayesian_network: Inference, Dynamic System, Markov Chain, Hidden Markov Model
- game_theory: Framework, Nash Equilibrium, Pareto Optimal