• Stars
    star
    515
  • Rank 85,879 (Top 2 %)
  • Language
    R
  • License
    Other
  • Created over 4 years ago
  • Updated 4 months ago

Reviews

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

Repository Details

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

modeltime

CRAN_Status_Badge R-CMD-check Codecov test coverage

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


Meet the modeltime ecosystem

Learn a growing ecosystem of forecasting packages

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

More Repositories

1

free_r_tips

Free R-Tips is a FREE Newsletter provided by Business Science. It comes with bite-sized code tutorials every week.
HTML
1,267
star
2

tidyquant

Bringing financial analysis to the tidyverse
R
850
star
3

pytimetk

Time series easier, faster, more fun. Pytimetk.
Python
673
star
4

timetk

Time series analysis in the `tidyverse`
R
608
star
5

anomalize

Tidy anomaly detection
R
337
star
6

tibbletime

Time-aware tibbles
R
179
star
7

presentations

A central repository of Business Science presentations
HTML
165
star
8

sweep

Extending broom for time series forecasting
R
155
star
9

correlationfunnel

Speed Up Exploratory Data Analysis (EDA)
R
132
star
10

cheatsheets

101
star
11

free_python_tips

HTML
79
star
12

modeltime.ensemble

Time Series Ensemble Forecasting
R
73
star
13

alphavantager

A lightweight R interface to the Alpha Vantage API
R
69
star
14

riingo

An R interface to the Tiingo stock price API
R
51
star
15

10_python_r_business_problems

Python
48
star
16

modeltime.h2o

Forecasting with H2O AutoML. Use the H2O Automatic Machine Learning algorithm as a backend for Modeltime Time Series Forecasting.
R
40
star
17

modeltime.gluonts

GluonTS Deep Learning with Modeltime
R
39
star
18

portfoliodown

An R package for creating professional data science portfolios
CSS
37
star
19

gpu_accelerated_forecasting_modeltime_gluonts

GPU-Accelerated Deep Learning for Time Series using Modeltime GluonTS (Learning Lab 53). Event sponsors: Saturn Cloud, NVIDIA, & Business Science.
HTML
22
star
20

modeltime.resample

Resampling Tools for Time Series Forecasting with Modeltime
R
19
star
21

reports

A central repository of Business Science technical reports
17
star
22

workshop_2018_dsgo

DataScienceGO 2018 - Machine Learning Workshop
R
13
star
23

lab_59_cust_lifetime_py

Learning Lab 59: Customer Lifetime Value Python
Python
12
star
24

pymodeltime

Pymodeltime offers a unified framework tailored to address a broad spectrum of requirements, including time series forecasting and various machine learning models.
Python
12
star
25

awesome-generative-ai

A curated list of resources for building and deploying generative AI specifically focusing on helping you become a GenAI developer with LLMs
12
star
26

shinyauth

Dockerfile
Dockerfile
10
star
27

gammodels

The parsnip backend for GAM Models.
R
7
star
28

modeltime_h2o_workshop

R
6
star
29

webinar_introducing_pytimetk

Jupyter Notebook
5
star
30

lab_50_lightgbm

Learning Lab 50: Hierarchical Forecasting
R
5
star
31

free_ai_training

Free training to get you started learning AI for data science today!
Jupyter Notebook
5
star
32

workshop_timetk_data_viz

R
3
star
33

bsu-dev

Code for development of Business Science University courses.
3
star
34

lab_63_nested_modeltime

R
1
star
35

courseinfo

Course information, curriculum, and brochures
1
star