Problem
Game logs are noisy, sequential, and difficult to interpret without feature engineering and visual feedback.
UpcomingMachine learningData analysisFrontend visualization
Poker Behavior Modeling
The upgraded project will frame predictive modeling as a usable analysis product: structured data pipelines, model evaluation, scenario exploration, and visual explanations for how player behavior changes across game contexts.
Signal
Behavior features
Signal
Action prediction
Signal
Interactive dashboard
Case study
What this project demonstrates
Approach
- Build clean features from game histories and player actions.
- Compare predictive models with transparent evaluation.
- Add dashboard controls that explain scenarios without requiring notebook reading.
Outcome
- Will broaden the portfolio with predictive analytics and interactive visualization.
- Will create a clear data-science-to-product story for mainstream CS roles.
Stack
Technology used or planned
Tooling belongs here, where it supports the project story instead of crowding the homepage hero.
PythonPyTorchPandasVisualization