https://github.com/alfarseniko/ai_weather_prediction_2020

A comparison between two predictive models to determine their accuracy.
https://github.com/alfarseniko/ai_weather_prediction_2020

ai built civil environment interdisciplinary learning machine

Last synced: about 1 month ago
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A comparison between two predictive models to determine their accuracy.

• Host: GitHub
• URL: https://github.com/alfarseniko/ai_weather_prediction_2020
• Owner: alfarseniko
• Created: 2024-05-22T10:21:21.000Z (7 months ago)
• Default Branch: main
• Last Pushed: 2024-06-01T06:42:35.000Z (7 months ago)
• Last Synced: 2024-06-02T08:01:21.437Z (7 months ago)
• Topics: ai, built, civil, environment, interdisciplinary, learning, machine
• Language: Jupyter Notebook
• Homepage: https://www.kaggle.com/datasets/berkeleyearth/climate-change-earth-surface-temperature-data
• Size: 1.95 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: readme.md

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README

        
This project was made for my elective course "AI in the Built Environment".

The goal was to create a prediction model for any civil engineering use. And then compare the two models (Random Forests and Neural Networks) for their accuracy.

The dataset was obtained from Kaggle (https://www.kaggle.com/datasets/berkeleyearth/climate-change-earth-surface-temperature-data).