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AhmedElkomi/DEPI-Predictive-Maintenance-Project

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This project is part of the DEPI Scholarship initiative and focuses on utilizing machine learning techniques to predict machine failures and enhance maintenance efficiency. By leveraging historical data and predictive analytics, this project aims to reduce unplanned downtime and optimize industrial processes.

active 2024-11-232024-11-27 (UTC)

Complete coverage27,179 / 27,181 hourly files (100%) · 2 absent upstream2023-08-152026-09-20 (UTC)
Events
8
Pushes
5
Pull requests
0
Issues
0
Stars
0
Forks
1

Activity over time

Daily event counts in the loaded window

Line chart, 5 days from 2024-11-23 to 2024-11-27. Pushes: 5 total, peak 5 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
AhmedElkomi5500

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.