Implement a linear regression model to predict house prices using features such as square footage, the number of bedrooms, and bathrooms. This model will learn the relationship between these features and house prices, providing a way to estimate the price of a house given its characteristics.
active 2024-09-17 → 2024-09-28 (UTC)
Activity over time
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Line chart, 12 days from 2024-09-17 to 2024-09-28. Pushes: 5 total, peak 4 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 0 total, peak 0 in a day. Comments: 0 total, peak 0 in a day. Stars: 0 total, peak 0 in a day.
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Top contributors
Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity
| Contributor | Contributions | Pushes | PRs | Comments |
|---|---|---|---|---|
| NadaEssam37 | 5 | 5 | 0 | 0 |
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Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 0 stars here means stars gained during the window, not the repo's star count.