Tidy time series forecasting with
For those that prefer video tutorials, we have an 11-minute YouTube Video that walks you through the Modeltime Workflow.
(Click to Watch on YouTube)
Getting Started with
A walkthrough of the 6-Step Process for using
modeltime to forecast
how to use
modeltime, find Modeltime Models, and
modeltime so you can use new algorithms inside the
install.packages("modeltime", dependencies = TRUE)
remotes::install_github("business-science/modeltime", dependencies = TRUE)
Modeltime unlocks time series models and machine learning in one framework
No need to switch back and forth between various frameworks.
unlocks machine learning & classical time series analysis.
A streamlined workflow for forecasting
Modeltime incorporates a streamlined workflow (see Getting Started with Modeltime) for using best practices to forecast.
Learn a growing ecosystem of forecasting packages
Modeltime is part of a growing ecosystem of Modeltime forecasting packages.
Modeltime is an amazing ecosystem for time series forecasting. But it can take a long time to learn:
Your probably thinking how am I ever going to learn time series forecasting. Here’s the solution that will save you years of struggling.
Become the forecasting expert for your organization
Time series is changing. Businesses now need 10,000+ time series forecasts every day. This is what I call a High-Performance Time Series Forecasting System (HPTSF) - Accurate, Robust, and Scalable Forecasting.
High-Performance Forecasting Systems will save companies by improving accuracy and scalability. Imagine what will happen to your career if you can provide your organization a “High-Performance Time Series Forecasting System” (HPTSF System).
I teach how to build a HPTFS System in my High-Performance Time Series Forecasting Course. You will learn:
Modeltime- 30+ Models (Prophet, ARIMA, XGBoost, Random Forest, & many more)
Become the Time Series Expert for your organization.
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