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Prediction of Grand Exchange prices with Recurrent Neural Networks

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OSRS Grand Exchange Price Prediction

Start-to-end project where we attempt to harness the power of machine learning to predict Old-school Runescape Grand Exchange prices.

Getting started

The journey so far has been documented in a series of Youtube videos found here:

  1. Part 1 - Setup and initial trial
  2. Part 2 - Data Collection
  3. Part 3 - Feature Engineering and Selection
  4. Part 4 - Hyperparameter Tuning, Application and API

Prerequisites

Dependencies install

python /path/to/GEPrediction-OSRS/setup.py install --user

Usage

Creating you own models

  1. Change the items_to_predict array in the main() function to the items you wish to use.
  2. Then, run:
python models.py
  1. You should see the .h5 model file created in the models folder along with features.txt file in the models/features folder

Applying the created models

  1. Make sure you have the latest item list, change the list of items in the main() function in line 98 of application.py
  2. Change the items_to_predict array in the main() function to match the models you created/have.
  3. Then, run:
python application.py
  1. You should see a .csv file created (or have data appended to) in the name of that item in data/predictions.

Running the flask app

  1. Change items in items_predicted array in index() to match the items that you've predicted on
  2. Run:
python flask-app.py
  1. Go to localhost:80 and see your results!

Running the jupyter notebooks

  1. Move the preferred notebook out of the Notebooks foler to the main directory
  2. Run the following command:
jupyter notebook

Scraping your own data

If you wish to scrape your own data, run the following script every 30 minutes (runelite):

python runelite_ge_scraper.py

You can do this automatically by using crontab (*/30 * * * *) if you're on a Linux machine or windows scheduler if you're on a Windows machine.

Credits

Contributions

  • ChronicCoder#1667, RusticPotatoes

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