https://github.com/mariamagro/bayesian_case_study

This case study focuses on predicting hazardous Near-Earth Objects (NEOs) using a dataset from NASA. It involves preprocessing the data, selecting key features, and applying both frequentist and Bayesian logistic regression models to predict the danger posed by NEOs.
https://github.com/mariamagro/bayesian_case_study

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This case study focuses on predicting hazardous Near-Earth Objects (NEOs) using a dataset from NASA. It involves preprocessing the data, selecting key features, and applying both frequentist and Bayesian logistic regression models to predict the danger posed by NEOs.

• Host: GitHub
• URL: https://github.com/mariamagro/bayesian_case_study
• Owner: mariamagro
• Created: 2024-08-13T21:02:04.000Z (5 months ago)
• Default Branch: main
• Last Pushed: 2024-08-18T18:21:20.000Z (5 months ago)
• Last Synced: 2024-08-18T19:37:03.212Z (5 months ago)
• Language: HTML
• Size: 3.12 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:

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