feat: add dual-model workflow notebook with LGBModel and ALSTM

[chenminghui1]

Summary

• Add examples/my_workflow_visual.ipynb demonstrating a complete quantitative research pipeline with LGBModel + ALSTM side-by-side comparison
• Remove *.ipynb from .gitignore so notebooks can be tracked in version control

Notebook features

• Dynamic date cutoff: 3 PM rule — after market close uses today's data, otherwise yesterday's
• Dual model training: LGBModel (Alpha158) and ALSTM (Alpha360) trained independently
• Dual backtest comparison: Both models backtested side-by-side with cumulative return curves overlaid
• Auto-select best model: Automatically picks the better-performing model based on backtest returns for final stock recommendations
• Top 20 stock recommendations: Visualized with bar charts and score distribution histograms
• Chinese font support: SimHei/Microsoft YaHei/DejaVu Sans fallback for matplotlib charts

Files changed

File	Change
examples/my_workflow_visual.ipynb	New dual-model workflow notebook (1030 lines)
.gitignore	Remove *.ipynb rule to allow notebook tracking
qlib/backtest/exchange.py	Lower default trading costs

Test plan

• LGBModel training and prediction executes without error
• ALSTM training completes (requires torch, Alpha360 uses 6-feat x 60-day time series)
• Dual backtest produces comparison metrics and charts
• Best model auto-selection logic works correctly
• Chinese characters render correctly in matplotlib output

🤖 Generated with Claude Code

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