Here's an improved version: Greetings! I've developed a straightforward linear regression model from scratch to predict house prices in Bangalore. But before delving into coding, let me walk you through the algorithm's conceptualization. I considered various factors such as location, ocean proximity, plot size, finished state, and flat type.
active 2024-05-06 → 2024-05-06 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 1 days from 2024-05-06 to 2024-05-06. Pushes: 1 total, peak 1 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 |
|---|---|---|---|---|
| ANSHPG | 1 | 1 | 0 | 0 |
Recent activity
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No issue or PR events — this repo's activity is pushes only.
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.