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business-science
309 Stars 45 Forks Other 575 Commits 14 Opened issues

Description

Modeltime unlocks time series forecast models and machine learning in one framework

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modeltime

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Tidy time series forecasting with

tidymodels
.

Quickstart Video

For those that prefer video tutorials, we have an 11-minute YouTube Video that walks you through the Modeltime Workflow.

Introduction to Modeltime

(Click to Watch on YouTube)

Tutorials

Installation

CRAN version:

install.packages("modeltime", dependencies = TRUE)

Development version:

remotes::install_github("business-science/modeltime", dependencies = TRUE)

Why modeltime?

Modeltime unlocks time series models and machine learning in one framework

No need to switch back and forth between various frameworks.

modeltime
unlocks machine learning & classical time series analysis.
  • forecast: Use ARIMA, ETS, and more models coming (
    arima_reg()
    ,
    arima_boost()
    , &
    exp_smoothing()
    ).
  • prophet: Use Facebook’s Prophet algorithm (
    prophet_reg()
    &
    prophet_boost()
    )
  • tidymodels: Use any
    parsnip
    model:
    rand_forest()
    ,
    boost_tree()
    ,
    linear_reg()
    ,
    mars()
    ,
    svm_rbf()
    to forecast

Forecast faster

A streamlined workflow for forecasting

Modeltime incorporates a streamlined workflow (see Getting Started with Modeltime) for using best practices to forecast.


A streamlined workflow for forecasting

A streamlined workflow for forecasting


Meet the modeltime ecosystem

Learn a growing ecosystem of forecasting packages

The modeltime ecosystem is growing

The modeltime ecosystem is growing

Modeltime is part of a growing ecosystem of Modeltime forecasting packages.

Summary

Modeltime is an amazing ecosystem for time series forecasting. But it can take a long time to learn:

  • Many algorithms
  • Ensembling and Resampling
  • Machine Learning
  • Deep Learning
  • Scalable Modeling: 10,000+ time series

Your probably thinking how am I ever going to learn time series forecasting. Here’s the solution that will save you years of struggling.

Take the High-Performance Forecasting Course

Become the forecasting expert for your organization

High-Performance Time Series Forecasting Course

High-Performance Time Series Course

Time Series is Changing

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).

How to Learn High-Performance Time Series Forecasting

I teach how to build a HPTFS System in my High-Performance Time Series Forecasting Course. You will learn:

  • Time Series Machine Learning (cutting-edge) with
    Modeltime
    - 30+ Models (Prophet, ARIMA, XGBoost, Random Forest, & many more)
  • Deep Learning with
    GluonTS
    (Competition Winners)
  • Time Series Preprocessing, Noise Reduction, & Anomaly Detection
  • Feature engineering using lagged variables & external regressors
  • Hyperparameter Tuning
  • Time series cross-validation
  • Ensembling Multiple Machine Learning & Univariate Modeling Techniques (Competition Winner)
  • Scalable Forecasting - Forecast 1000+ time series in parallel
  • and more.

Become the Time Series Expert for your organization.


Take the High-Performance Time Series Forecasting Course

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