🚀 Pro Edition → Book + Bonus Pack Mastering Modern Time Series Forecasting 🔥 The Complete Guide to Statistical, Machine Learning & Deep Learning Models in Python — Now with Premium Tools, Templates & Real-World Case Studies

🔥 Pro Edition: Mastering Modern Time Series Forecasting (Early Access)

The elite version of the book — trusted by data science leaders in 100+ countries.
Unlock the premium toolkit behind today’s most powerful forecasting systems.

🚀🚀🚀 New: Pro Edition Now Available — $65 (USD) 🔥🔥🔥
Includes everything in the standard edition plus: premium forecasting templates, cheat sheets, extended case studies, behind‑the‑scenes notebooks, model tuning toolkits, and access to live Q&A + AMA sessions with the author.
⚠️ Final price of Pro Edition will rise to $150+ at book completion.

See 📦 What You Get and 💸 Pricing for full details.

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

Let’s face it — most forecasting books fall short in one way or another. Many are outdated, overly simplistic, or written by authors without hands-on experience building real-world forecasting systems. While a few classics stand out, they tend to focus solely on traditional methods — often geared toward beginners (like Hyndman) or buried under a thousand pages of dense theory (like Hamilton).

Plenty of resources cover classical techniques or dive deep into theoretical details, but they rarely go the distance in offering practical guidance — especially when it comes to modern tools like machine learning, deep learning, and production-ready systems.

Even some newer books that try to bridge this gap often end up skimming the surface. They offer high-level overviews without the depth or practical insights needed to build forecasting solutions that actually work in real-world environments. Worse, they often skip foundational concepts entirely — making it easy for readers to follow copy-paste recipes without understanding what’s really going on.

The result? Fragile systems that seem fine in testing, but fall apart under real-world pressure.

If you’ve ever felt confused by unexplained code, frustrated by missing fundamentals, or unsure how to move from theory to application — you’re not alone.

This book is different.

Mastering Modern Time Series Forecasting is a complete, hands-on guide that blends statistical, machine learning, and deep learning approaches — all grounded in real-world experience. It’s built to be clear, thorough, and practical from start to finish.

Whether you're just beginning your journey or leading forecasting initiatives at scale, this book gives you the tools, understanding, and workflows to build systems that make a real impact — and actually hold up in production.

✍️ About the Author

Written by Valeriy Manokhin, PhD, MBA, CQF — a seasoned forecasting expert, data scientist, and machine learning researcher with publications in top academic journals.

Valeriy has advised both startups and large enterprises, helping them build and rebuild forecasting systems at scale. He has led successful forecasting initiatives for global organizations — including winning competitive tenders from multinational companies, outperforming major consulting firms like BCG and specialized AI startups focused on forecasting. He has delivered production-grade solutions for industry leaders such as Stanley Black & Decker and GfK.

His methods have driven multimillion-dollar business impact, and his training programs have reached professionals in over 30 countries. This book is now used in more than 100+ countries and has become a #1-ranked title in Machine Learning, Forecasting, and Time Series across major platforms.

🌍 Trusted By and Taught To

Valeriy’s expertise is trusted by leaders at:
Amazon, Apple, Google, Meta, Nike, BlackRock, Morgan Stanley, Target, NTT Data, Mars Inc., Lidl, Publicis Sapient, and more.

His frameworks are followed by professionals from:
University of Chicago, KTH (Sweden), UBC (Canada), DTU (Denmark), and other world-class institutions.

👤 Students include:
VPs of Engineering, AI Leads, Principal & Lead Data Scientists, ML Engineers, Consultants, Professors, Founders, Researchers, and PhD students.

🎓 Want a Live, Interactive Learning Experience?

Pair this book with the Modern Forecasting Mastery course on Maven.
Join live cohort sessions with Valeriy, get direct feedback, and build models with peers.
Next cohort opens soon → maven.com/valeriy-manokhin/modern-forecasting-mastery

🔍 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 models — with code you can actually use.

🤖 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 large, domain‑general pre‑trained models (“GPT for time series”) with full implementation insights.

🎯 Probabilistic & Interpretable Forecasting
Move beyond point forecasts using techniques like conformal prediction, SHAP, attention, and explainability tools.

📊 Real‑World Case Studies
Retail, energy, finance — apply what you learn to live datasets and market scenarios.

👥 Who It’s For

• Data Scientists & ML Engineers building real-world forecasting systems
• Analysts & Developers looking for practical, hands-on code and frameworks
• Students, Educators & Researchers seeking a modern and curriculum-ready reference
• Demand Planners & Business Strategists translating forecasts into action and ROI

🧠 Why This Book Stands Out

🔑 Forecasting models are just 5% of what it takes to build successful forecasting systems.

The remaining 95% — the hard-won knowledge about metrics, validation, deployment, failure modes, and real-world constraints — is either unavailable or drowned out in a sea of internet noise and social media fluff.

🔍 It starts with what actually matters: solid foundations.
That means learning how to evaluate forecasts properly, understand when they're broken, and build with confidence — not on shaky assumptions, but on methods that hold up under real-world pressure.

🧠 Focuses on understanding, not just coding
Understand model mechanics and decision-making—not black-box training code.

💻 Fully documented, transparent code
No obfuscation. Every example is explainable, reusable, and production-ready.

🔄 Continuously improved with reader feedback
This is a living resource, shaped by an ongoing review process involving a wide community of readers who provide thoughtful, real-world feedback. Many improvements, clarifications, and additions come directly from this collaboration. Thank you to all the reviewers — your contributions are acknowledged and appreciated in the book. Readers receive lifetime updates, including new chapters and bonus tools.

📚 Comprehensive, real-world coverage
From classical statistical models to deep learning and forecasting-specific transformers (FTSMs), this book covers it all — with a focus on what actually works. Every method included has been battle-tested in real-world projects or validated against robust academic benchmarks. No esoteric fluff — just practical tools and approaches that deliver results in production.

📈 Real ROI — for your company and your career
Readers consistently report fast, tangible improvements in model accuracy, interpretability, and stakeholder confidence — often within weeks. No more forecasting models that silently fail or production systems that collapse under pressure. This book helps you build solutions that earn trust, drive business impact, and advance your career — not frustrate clients or burn out data science teams.

📦 What You Get

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

🔓 Pro Edition Bonus Pack (Early Access – $65)

Includes everything above, plus:

✅ Premium Forecasting Templates — plug-and-play workflows
✅ Extended Case Studies — deep analyses across major industries
✅ Cheat Sheets & Flashcards — quick-reference model guides and best practices
✅ Behind-the-Scenes Notebooks — annotated walkthroughs and exploratory pipelines
✅ Forecast Model Selection Toolkit — Python notebooks to benchmark, optimize, and compare

📈 Ideal for professionals and teams who want to build and deploy faster—and sidestep the guesswork.

💸 Pricing

🎉 Standard Edition Price: $40 | Minimum: $35
Will increase to $80+ as content grows.

🚀 Pro Edition Early Access: Price: $70 | Minimum: $35
Includes the full book + Premium Pack.
✅ Lock in now—price will rise to $150+ at full release.

A tremendous amount of work and expertise has gone into this book, which is designed to deliver exponential improvement to your forecasting skills, your company's bottom line and ROI, and your career. Forecasting is one of the most in-demand skills across nearly every industry today.

As the content continues to grow, if you find value in it—or simply want to support the project—you're welcome to contribute whatever it’s worth to you ❤️.

Ready to take your forecasting skills from stats to neural nets—and from theory to high-impact deployment?

👉 Hit Buy Now, and if you want structured support, check out the course at
maven.com/valeriy-manokhin/modern-forecasting-mastery