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In an era where clean water is increasingly scarce, ensuring the potability of available water sources is paramount for public health and environmental sustainability. Our project aims to leverage the power of machine learning to develop a predictive model capable of accurately assessing the potability of water samples.

active 2024-02-182024-06-10 (UTC)

Complete coverage27,119 / 27,121 hourly files (100%) · 2 absent upstream2023-08-152026-09-18 (UTC)
Events
11
Pushes
5
Pull requests
0
Issues
0
Stars
0
Forks
0

Activity over time

Daily event counts in the loaded window

Line chart, 114 days from 2024-02-18 to 2024-06-10. Pushes: 5 total, peak 3 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.

  • Pushes
  • Pull requests
  • Issues
  • Comments
  • Stars

Top contributors

Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity

ContributorContributionsPushesPRsComments
inki695500

Recent activity

Latest issues, pull requests and releases

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.