About the Book

📘 Mastering Modern Time Series Forecasting (early access - release in 2025)

This book will rise to $59+ as more chapters drop. Preorder now for $25 and lock in lifetime access.

The Definitive Guide to Statistical, Machine Learning & Deep Learning Models in Python

Let’s be honest — most forecasting books are either outdated, too shallow, or written by folks who’ve never actually built a real forecasting system.

If you’ve ever felt frustrated by books that skip the basics, toss in code without explaining it, or barely touch on what forecasting really involves — you’re not alone.

This is different.

Mastering Modern Time Series Forecasting is your all-in-one, no-shortcuts guide to building reliable, high-impact forecasting systems. Whether you're just getting started or looking to deepen your expertise, this book takes you from rock-solid foundations to the latest advances in forecasting — including deep learning, transformers, and FTSM (Foundational Time Series Models).

Written by a practitioner with over a decade of experience, who’s built production-grade forecasting systems for multibillion-dollar companies, this book is grounded in reality — not hype. The systems I’ve helped build have delivered multimillion-dollar business value, but I’ve also seen the other side: data science teams chasing shiny tools, only to ship systems that crash in production, fail silently, or burn through budgets without results.

This book is a response to that — combining practical Python examples, real-world case studies, and a clear path to building forecasting solutions that actually work, scale, and deliver value.

🔍 What You'll Learn

📘 Core Forecasting Foundations

Grasp what forecast accuracy really means, master model validation strategies, and sidestep common pitfalls that trip up even experienced practitioners.

📈 Classical Models, Done Right

In-depth, modern takes on ARIMA, Exponential Smoothing, and other classical statistical and econometrics models — with clarity, not complexity.

🤖 Machine Learning for Time Series

Build feature-rich forecasts using state-of-the-art ML techniques that go far beyond black-box models.

🧠 Deep Learning & Transformers

Explore powerful deep learning architectures, including Transformer-based models — all with clear, readable PyTorch code.

📊 FTSMs – Foundational Time Series Models

Explore the rise of Foundational Time Series Models (FTSMs) — large, pre-trained models designed to generalize across domains, tasks, and time horizons. Think GPT for time series.

🎯 Probabilistic & Interpretable Forecasting

Move beyond point forecasts with uncertainty quantification, conformal prediction, SHAP, attention mechanisms, and explainability tools.

📊 Real-World Case Studies

Apply what you’ve learned on practical datasets across domains like retail, energy, and finance.

🚀 MLOps & Deployment

Learn how to deploy, monitor, and scale your forecasting pipelines in the real world — without the headaches.

👥 Who It’s For

• Data Scientists & ML Engineers
• Solving real-world forecasting challenges and building production-ready systems.
• Analysts & Developers
• Looking for a practical, hands-on reference that covers both fundamentals and advanced techniques.
• Students, Educators & Researchers
• In need of a modern, curriculum-friendly resource grounded in both theory and application.
• Demand Planners & Business Strategists
• Focused on delivering real value through accurate, actionable forecasts.

🧠 Why This Book Stands Out

• 🔍 Starts with what matters — metrics and validation
• Before jumping into models, you’ll learn how to evaluate them properly so you’re building on a solid foundation.
• 🧠 Focuses on understanding, not just coding
• Learn how methods work, why they work, and when to use them — not just how to run the code.
• 💻 Fully documented, transparent code
• No black boxes. Every example is clearly explained so you can learn and adapt, not guess.
• 🔄 Updated continuously with reader feedback
• Buy once, benefit forever — you’ll get lifetime updates as the field evolves.
• 📚 Everything in one place
• From classical models to deep learning and FTSMs — no need to juggle multiple resources ever again.

📦 What You Get

• Instant download of the full book
• All code examples, datasets, and notebooks
• Free lifetime updates (including new chapters, errata fixes, and bonus content)
• Exclusive early access to upcoming bonus chapters & Q&A sessions

💸 Pricing

• 🎉 Introductory Launch Price Suggested: $35 | Minimum: $30
• This is the initial price — it will increase as more chapters, tools, and content are released.
• If you find value or want to support the project, feel free to pay what it’s worth to you ❤️

Ready to take your forecasting skills from stats to neural nets, and from theory to real-world deployment?

👉 Hit “Buy Now” and start mastering forecasting like never before.

About the Author

Valery Manokhin

@predict_addict

Valery Manokhin, PhD, MBA, CQF is Senior Data Science and AI Leader with over a decade of experience driving transformative machine learning solutions across global enterprises. Recognized author and educator in machine learning, AI, advanced forecasting, uncertainty quantification, with a proven track record of aligning data strategies with business objectives to deliver significant, measurable business outcomes.