Yu-ChangCheng/manufacturing-forecasting-framework
- Total stars
- 73
- Today · UTC
- —No data
More actions
Reproducible monthly demand forecasting with Random Forest, chronological backtests, transparent baselines, and a guided local app.
Save to My finds to follow releases and star growth. Saved in this browser.
About the project
A reproducible framework for monthly item-level demand forecasting with Random Forest, chronological backtests, simple baselines, and a local Streamlit app for uploading CSV/Excel files.
Useful for
- Upload your own CSV or Excel demand data and get a forecast with a report via the local app
- Compare Random Forest against last-month and same-month-last-year baselines on a rolling-origin backtest
- Configure lag/rolling/calendar features and train a model in the Jupyter notebook on your data
README summarized by DeepSeek V4.1 Flash. Details may be inaccurate.
Star growth looks organic. Data as of October 9, 2026, 00:17 UTC.
The star-growth assessment does not verify whether the project is safe to run.
Stars per day
Bars show daily stars; the line is a moving average of the available history. Short histories do not yet establish a reliable usual pace. Red marks spike days.
Why it’s trending
- There are not enough fresh counter measurements for today's UTC day. The gain is unknown.
- The repository is 2 days old and already has 73 stars. With less than two weeks of history, there's no usual pace to compare the spike against yet.
- Top new repositories this week: #194.
- About 240 forks a day — people are taking the code.
Three GitHub discoveries in each edition
What they do, why they are gaining interest, and what to check before using them.
Editions at 10:00, 16:00, 22:00 MSK.
Numbers
- Total stars
- 73
- Today
- Not enough measurements today
- Forks
- 13
- Issues and pull requests
- 0
- Watchers
- 0
- Language
- Python
- License
- MIT
- Created
- October 7, 2026
- Last push
- October 7, 2026
Star trust
Growth looks organic: forks and discussion are in line with active projects, and stars arrive unevenly, the way people give them.
These are heuristics, not a verdict: we judge by the repository’s behavior, not by a list of stargazers.
Spotted in
- October 9, 2026Top new repositories this week: #194