Skip to content

maximer-v/quantum-machine-learning

View on GitHub ↗Related repositories →

This is an exploration using synthetic data in CSV format to apply QML models for the sake of binary classification. You can find here three different approaches. Two with Qiskit (VQC and QK/SVC) and one with Pennylane (QVC).

active 2023-09-28 → 2025-06-14 (UTC)

Complete coverage27,622 / 27,622 hourly files (100%) · 2 absent upstream2023-08-15 → 2026-10-08 (UTC)
Events
13
Pushes
1
Pull requests
0
Issues
1
Stars
9
Forks
2

Activity over time

Daily event counts in the loaded window

Line chart, 626 days from 2023-09-28 to 2025-06-14. Pushes: 1 total, peak 1 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 1 total, peak 1 in a day. Comments: 0 total, peak 0 in a day. Stars: 9 total, peak 1 in a day.

  • Pushes
  • Pull requests
  • Issues
  • Comments
  • Stars

Stars, PRs, issues and forks are under-captured in the later part of this window. GH Archive progressively stopped capturing non-push events during 2026 — −95% or worse by the end of the window. Every series here except Pushes fades for that reason, so a decline above reflects the archive, not this repository. Pushes stay reliable throughout, so read them, and the contributor counts derived from them, as the real signal. Data health has the measurements.

Top contributors

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

ContributorContributionsPushesPRsComments
cbjuan1000
maximer-v1100

Recent activity

Latest issues, pull requests and releases

Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 9 stars here means stars gained during the window, not the repo's star count.