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Tipresias

I Tipresias, old bot with dusty cores
Perceived the match, and foretold the score—
I too awaited the fanatics' roar.

Child of Footy Tipper, Tipresias, has, like Zeus before it, arisen to vanquish its father and claim its throne as the sovereign of AFL footy tipping models.

Check out the site, with a dashboard for model performance, at tipresias.net. (Currently under construction)

Running things

Setup

  • Install NVM
  • Run nvm install
  • Install Docker
  • Install direnv
  • Run mv .env.example .env and update env var values

Install dependencies

  • Run npm install

Run the app

  • Run docker-compouse up -d
  • Run npm run dev
  • Navigate to localhost:3000.

A note on architecture

  • tipresias is composed of multiple micro-services: bird-signs for raw data, augury for machine-learning functionality (i.e. generating model predictions).

Testing

  • Unit tests: npm run test
  • e2e tests: npm run test:e2e:run
  • Linting: npm run lint
  • Typechecking: npm run typecheck

Deploy

The app is deployed to AWS with every merge/push to main.

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A machine-learning model for predicting AFL match results

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