LSTM-Time-Series-Forecasting AmirhosseinHonardoust · COMPLETED
A hands-on project for forecasting time-series with PyTorch LSTMs. It creates realistic daily data (trend, seasonality, events, noise), prepares it with sliding windows, and trains an LSTM to make multi-step predictions. The project tracks errors with RMSE, MAE, MAPE and shows clear plots of training progress and forecast results.
github.com/AmirhosseinHonardoust/LSTM-Time-Series-Forecasting · ★ 28 · Forks 2 · Size 504 KB
SUMMARY
Technologies 9
Scored 9
Observed 9
Practices 6
Evidence 11
Skips 0
COVERAGE
Analyzed 29 files · 45 commits · 0 API calls
TECHNOLOGIES & DEPTH
TOML LANGUAGE Depth 70
1 files · PRODUCTION
Markdown LANGUAGE Depth 70
5 files · PRODUCTION
YAML LANGUAGE Depth 70
2 files · PRODUCTION
Python LANGUAGE Depth 70
15 files · PRODUCTION
pip BUILD_TOOL Depth 80
1 files · CONFIGURATION
Poetry BUILD_TOOL Depth 80
1 files · CONFIGURATION
NumPy LIBRARY Depth 81
6 files · PRODUCTION, TEST
pandas LIBRARY Depth 81
5 files · PRODUCTION, TEST
pytest TESTING Depth 45
3 files · TEST
PRACTICES
documentation · observedautomated_tests · observedcontinuous_integration · observedcontainerization · absentlinting · observedformatting · absent
ACTIVITY & OWNERSHIP
First commit 2025-09-11
Last commit 2026-09-06
Active months 3
Commits 45