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#timeseries

24 posts8 participants0 posts today
Continued thread
Public
Valeriy M., PhD, MBA, CQF

Preorder now → [Mastering Modern TimeSeries Forecasting](valeman.gumroad.com/l/Masterin)
Let’s shape the future — one forecast at a time. ⚡📊
#TimeSeries #Forecasting #DataScience #MachineLearning #Preorder #NewBook #TechCommunity

GumroadMastering Modern Time Series Forecasting : A Comprehensive Guide to Statistical, Machine Learning, and Deep Learning Models in Python📘 Mastering Modern Time Series Forecasting (preorder - release in 2025)The Definitive Guide to Statistical, Machine Learning & Deep Learning Models in PythonLet’s be honest — most forecasting books are either outdated, too shallow, or written by folks who’ve never actually built a real forecasting system.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 ModelsExplore 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 EngineersSolving real-world forecasting challenges and building production-ready systems. Analysts & DevelopersLooking for a practical, hands-on reference that covers both fundamentals and advanced techniques. Students, Educators & ResearchersIn need of a modern, curriculum-friendly resource grounded in both theory and application. Demand Planners & Business StrategistsFocused on delivering real value through accurate, actionable forecasts. 🧠 Why This Book Stands Out 🔍 Starts with what matters — metrics and validationBefore jumping into models, you’ll learn how to evaluate them properly so you’re building on a solid foundation. 🧠 Focuses on understanding, not just codingLearn how methods work, why they work, and when to use them — not just how to run the code. 💻 Fully documented, transparent codeNo black boxes. Every example is clearly explained so you can learn and adapt, not guess. 🔄 Updated continuously with reader feedbackBuy once, benefit forever — you’ll get lifetime updates as the field evolves. 📚 Everything in one placeFrom 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: $29 | Minimum: $20 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.
Public *
binjr

binjr v3.22.0 is now available! 🎉

There is now an option to further refine the behaviour of empty tab panes, introduced in the previous release.
This release also addresses a couple of bugs and brings all dependencies up to date (including 24).

Full changelog and download links at binjr.eu

binjrbinjr - A Time Series Browserbinjr is a standalone time series browser. it renders time series data produced by other applications as dynamically editable charts and provides advanced features to navigate the data smoothly and efficiently.
#java#javafx#dataViz
Public
PaquitoBernard

I am looking for a postdoc 'Environmental and behavioral health in a changing climate' (1/2)

2 years in #Rennes #france #rstats #timeseries

We are looking for a postdoctoral researcher to help us understand the short-term impacts of environmental conditions on mental health, sleep and physical activity related behaviors. Future findings will help us better anticipate present and future consequences of climate change on bike use and sleep.

#academia#research#climatechange
Continued thread
Public
Valeriy M., PhD, MBA, CQF

Though I have previously attended university lectures on time series forecasting, I found your explanation to be far more accessible and engaging."

valeman.gumroad.com/l/Masterin

GumroadMastering Modern Time Series Forecasting : A Comprehensive Guide to Statistical, Machine Learning, and Deep Learning Models in Python📘 Mastering Modern Time Series Forecasting (preorder - release in 2025)The Definitive Guide to Statistical, Machine Learning & Deep Learning Models in PythonLet’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 ModelsExplore 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 EngineersSolving real-world forecasting challenges and building production-ready systems. Analysts & DevelopersLooking for a practical, hands-on reference that covers both fundamentals and advanced techniques. Students, Educators & ResearchersIn need of a modern, curriculum-friendly resource grounded in both theory and application. Demand Planners & Business StrategistsFocused on delivering real value through accurate, actionable forecasts. 🧠 Why This Book Stands Out 🔍 Starts with what matters — metrics and validationBefore jumping into models, you’ll learn how to evaluate them properly so you’re building on a solid foundation. 🧠 Focuses on understanding, not just codingLearn how methods work, why they work, and when to use them — not just how to run the code. 💻 Fully documented, transparent codeNo black boxes. Every example is clearly explained so you can learn and adapt, not guess. 🔄 Updated continuously with reader feedbackBuy once, benefit forever — you’ll get lifetime updates as the field evolves. 📚 Everything in one placeFrom 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: $29 | Minimum: $20 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.
#timeseries#forecasting
Continued thread
Public
Valeriy M., PhD, MBA, CQF

Preorder now → [Mastering Modern TimeSeries Forecasting](valeman.gumroad.com/l/Masterin)
Let’s shape the future — one forecast at a time. ⚡📊
#TimeSeries #Forecasting #DataScience #MachineLearning #Preorder #NewBook #TechCommunity

GumroadMastering Modern Time Series Forecasting : A Comprehensive Guide to Statistical, Machine Learning, and Deep Learning Models in Python📘 Mastering Modern Time Series Forecasting (preorder - release in 2025)The Definitive Guide to Statistical, Machine Learning & Deep Learning Models in PythonLet’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 ModelsExplore 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 EngineersSolving real-world forecasting challenges and building production-ready systems. Analysts & DevelopersLooking for a practical, hands-on reference that covers both fundamentals and advanced techniques. Students, Educators & ResearchersIn need of a modern, curriculum-friendly resource grounded in both theory and application. Demand Planners & Business StrategistsFocused on delivering real value through accurate, actionable forecasts. 🧠 Why This Book Stands Out 🔍 Starts with what matters — metrics and validationBefore jumping into models, you’ll learn how to evaluate them properly so you’re building on a solid foundation. 🧠 Focuses on understanding, not just codingLearn how methods work, why they work, and when to use them — not just how to run the code. 💻 Fully documented, transparent codeNo black boxes. Every example is clearly explained so you can learn and adapt, not guess. 🔄 Updated continuously with reader feedbackBuy once, benefit forever — you’ll get lifetime updates as the field evolves. 📚 Everything in one placeFrom 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: $29 | Minimum: $20 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.
Continued thread
Public
Valeriy M., PhD, MBA, CQF

👉 Get the early access edition here: valeman.gumroad.com/l/Masterin

GumroadMastering Modern Time Series Forecasting : A Comprehensive Guide to Statistical, Machine Learning, and Deep Learning Models in Python📘 Mastering Modern Time Series Forecasting (preorder - release in 2025)The Definitive Guide to Statistical, Machine Learning & Deep Learning Models in PythonLet’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 ModelsExplore 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 EngineersSolving real-world forecasting challenges and building production-ready systems. Analysts & DevelopersLooking for a practical, hands-on reference that covers both fundamentals and advanced techniques. Students, Educators & ResearchersIn need of a modern, curriculum-friendly resource grounded in both theory and application. Demand Planners & Business StrategistsFocused on delivering real value through accurate, actionable forecasts. 🧠 Why This Book Stands Out 🔍 Starts with what matters — metrics and validationBefore jumping into models, you’ll learn how to evaluate them properly so you’re building on a solid foundation. 🧠 Focuses on understanding, not just codingLearn how methods work, why they work, and when to use them — not just how to run the code. 💻 Fully documented, transparent codeNo black boxes. Every example is clearly explained so you can learn and adapt, not guess. 🔄 Updated continuously with reader feedbackBuy once, benefit forever — you’ll get lifetime updates as the field evolves. 📚 Everything in one placeFrom 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: $29 | Minimum: $20 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.
#forecasting#timeseries#machinelearning
Continued thread
Public
Valeriy M., PhD, MBA, CQF

…then this is for you.

🔗 Check it out here:
👉 valeman.gumroad.com/l/Masterin

Huge thanks to the reviewers and early readers who helped shape the launch. 🙏
More chapters are on the way!

GumroadMastering Modern Time Series Forecasting : A Comprehensive Guide to Statistical, Machine Learning, and Deep Learning Models in Python📘 Mastering Modern Time Series Forecasting (preorder - release in 2025)The Definitive Guide to Statistical, Machine Learning & Deep Learning Models in PythonLet’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 ModelsExplore 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 EngineersSolving real-world forecasting challenges and building production-ready systems. Analysts & DevelopersLooking for a practical, hands-on reference that covers both fundamentals and advanced techniques. Students, Educators & ResearchersIn need of a modern, curriculum-friendly resource grounded in both theory and application. Demand Planners & Business StrategistsFocused on delivering real value through accurate, actionable forecasts. 🧠 Why This Book Stands Out 🔍 Starts with what matters — metrics and validationBefore jumping into models, you’ll learn how to evaluate them properly so you’re building on a solid foundation. 🧠 Focuses on understanding, not just codingLearn how methods work, why they work, and when to use them — not just how to run the code. 💻 Fully documented, transparent codeNo black boxes. Every example is clearly explained so you can learn and adapt, not guess. 🔄 Updated continuously with reader feedbackBuy once, benefit forever — you’ll get lifetime updates as the field evolves. 📚 Everything in one placeFrom 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: $29 | Minimum: $20 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.
#timeseries#machinelearning#datascience
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