Interactive Notebooks¶
Get hands-on experience with OnlineRake through our comprehensive Jupyter notebooks!
These interactive notebooks provide complete tutorials with visualizations, real-time monitoring, and comprehensive examples that demonstrate the power of streaming weight calibration.
🚀 Getting Started¶
Perfect for newcomers to OnlineRake! Learn the basics with clear examples and visual proof that the algorithms work.
What you’ll learn:
Basic OnlineRake usage with SGD and MWU algorithms
Correcting feature bias in real-time survey data
Handling time-varying patterns in streaming data
Visual validation with comprehensive plots
Clear before/after comparisons showing success
⚡ Performance Comparison¶
Deep dive into algorithm performance across different bias scenarios.
What you’ll learn:
Comprehensive SGD vs MWU comparison
Testing across multiple bias patterns (linear, sudden, oscillating)
Performance metrics and statistical analysis
Algorithm selection guidance
Parameter tuning insights
🔬 Advanced Diagnostics¶
Master the monitoring and diagnostic capabilities for production deployments.
What you’ll learn:
Automatic convergence detection
Oscillation monitoring and problem diagnosis
Weight distribution evolution analysis
Real-time performance tracking
Production monitoring best practices
🎯 Quick Start Guide¶
Install dependencies:
pip install onlinerake[docs]Start with Getting Started: Master the basics first
Compare algorithms: Understand when to use SGD vs MWU
Learn diagnostics: Essential for production deployments
💡 Tips for Success¶
Run notebooks locally for the best interactive experience
Experiment with parameters to see their effects
Try your own data after completing the tutorials
Check diagnostics regularly in production environments
Each notebook is self-contained and includes all necessary imports and setup code. The visualizations clearly demonstrate that OnlineRake successfully corrects bias in streaming data!