# Machine Learning
5 posts
Teaching a Machine to Stock ATMs: Deep Reinforcement Learning for Cash Demand Forecasting
A PhD course project applying the Deep Deterministic Policy Gradient (DDPG) algorithm to ATM cash demand forecasting. The problem is framed as a continuous Markov Decision Process, evaluated against industry benchmarks on the 111-ATM NN5 dataset.
The Application of Hidden Markov Model to Detect BTC Market Regime
A research-oriented overview of how a Gaussian Mixture Hidden Markov Model can be used for BTC regime learning, with focus on theory, structure, and practical limitations.
Learning Optimal Pricing with Reinforcement Learning
A technical implementation of the Actor-Critic algorithm to solve dynamic pricing. This project benchmarks RL against theoretical optima to test its effectiveness in combinatorial optimization.
Analysis of State Schools in Scotland: K-Means Clustering by Deprivation Rate and Pupils Quantity
A data-driven analysis of 2,431 Scottish state schools using K-Means clustering to categorize local authorities by pupil density and SIMD deprivation scores to identify areas requiring NGO support.