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kaiwaehner/kafka-streams-machine-learning-examples

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This project contains examples which demonstrate how to deploy analytic models to mission-critical, scalable production environments leveraging Apache Kafka and its Streams API. Models are built with Python, H2O, TensorFlow, Keras, DeepLearning4 and other technologies.

active 2023-08-312026-04-19 (UTC)

Complete coverage27,090 / 27,092 hourly files (100%) · 2 absent upstream2023-08-152026-09-16 (UTC)
Events
119
Pushes
0
Pull requests
1
Issues
0
Stars
92
Forks
26

Activity over time

Daily event counts in the loaded window

Line chart, 963 days from 2023-08-31 to 2026-04-19. Pushes: 0 total, peak 0 in a day. Pull requests: 1 total, peak 1 in a day. Issues: 0 total, peak 0 in a day. Comments: 0 total, peak 0 in a day. Stars: 92 total, peak 5 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
JLLeitschuh1010

Recent activity

Latest issues, pull requests and releases

  • Pull request#24JLLeitschuh2023-12-17 23:31

Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 92 stars here means stars gained during the window, not the repo's star count.