🚀 Pro Edition (Book + Bonus Pack) Applied Conformal Prediction: Reliable Uncertainty Quantification for Real-World Machine Learning (Preorder / Early Access)
🚀 Applied Conformal Prediction: Practical Uncertainty Quantification for Real-World ML 🚀
Preorder / Early Access — chapters released progressively
Most ML systems don’t fail because the point prediction is wrong.
They fail because nobody knows when not to trust it.
Applied Conformal Prediction is a practitioner-focused guide to building models that output valid, decision-ready uncertainty — prediction intervals and prediction sets you can communicate, monitor, and defend in production.
This is not “uncertainty vibes” or toy examples. It’s conformal prediction as it’s used in real pipelines: strong baselines, practical workflows, and the failure modes that actually matter.
📖 What’s Inside
- Distribution-free uncertainty quantification with finite-sample coverage guarantees
- Conformal prediction for regression and classification (and where each breaks)
- Practical workflows: split conformal, CV+, conditional/Mondrian variants, and online settings
- Diagnostics & monitoring: coverage gaps, drift, non-IID data, leakage, and evaluation pitfalls
- Deployment guidance: how to integrate conformal outputs into real decision systems
🎯 Who It’s For
- Data Scientists & ML Engineers shipping models to production
- Researchers who want applied clarity and implementation-ready methods
- Practitioners in high-stakes domains (finance, risk, operations, regulated settings)
If you only care about leaderboard metrics, this won’t be your favorite book.
If you care about reliable decisions under uncertainty, it will.
⭐ Pro Edition (Recommended)
The Pro Edition is the complete package for professionals who want more than theory.
You get the full book plus a deployment-grade bonus pack designed to help you apply conformal prediction correctly — fast.
✅ What’s Included in the Pro Edition
- ✅ Full Digital Book — all chapters as they’re released
- ✅ Complete Jupyter Notebooks — end-to-end, production-ready Python code
- ✅ Extended Case Studies — real projects in finance, business, and beyond
- ✅ Advanced Methods — modern extensions beyond the basics
- ✅ Lifetime Updates — every new chapter and future edition included
- ✅ Final Print-Ready PDF — the polished compiled version at completion
Why Pro?
Core gives you the essentials.
Pro gives you the implementation playbook: code, workflows, diagnostics, and professional-grade examples.
With Pro, you’ll be able to:
- Build trustworthy prediction intervals/sets that hold up in practice
- Communicate uncertainty in a way stakeholders actually understand
- Avoid silent failure modes under shift, drift, and non-IID data
📅 Start today — secure Early Access and own the complete Pro package as it evolves.
Pro Edition (Book + Bonus Pack) Applied Conformal Prediction: Reliable Uncertainty Quantification for Real-World Machine Learning (Preorder / Early Access)