
Trader Train
This trains LSTM, Transformer, and N-BEATS models on market data through the neural-trader package. You pick a model type and ticker symbol, and it runs training with confidence intervals, validation metrics, and prediction horizons up to 5 days out. The model comparison mode is handy since you can test all three architectures against the same symbol in one go. Results get stored to the trading-analysis namespace and fed into SONA for pattern learning. It's solid for quick ML backtesting without writing training loops yourself, though you're still dependent on neural-trader's implementation choices under the hood.
- skills.sh installs
- 738
- GitHub stars
- 81.4K
- last updated
- Aug 21, 2026
Install
$ npx -y skills add ruvnet/ruflo --skill trader-train --agent claude-codeInstalls into .claude/skills of the current project.
Files
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Details
- Repository
- github.com/ruvnet/ruflo
- Category
- Productivity & Planning
- First seen
- Jun 3, 2026
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- Iot Witness Verify729
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