https://github.com/marcozanotti/tsforecasting-dashboard
Forecast App
https://github.com/marcozanotti/tsforecasting-dashboard
deep-learning forecasting machine-learning statistics timeseries
Last synced: 4 months ago
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Forecast App
- Host: GitHub
- URL: https://github.com/marcozanotti/tsforecasting-dashboard
- Owner: marcozanotti
- Created: 2024-01-22T17:32:50.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2025-09-30T23:23:10.000Z (9 months ago)
- Last Synced: 2025-10-25T12:54:55.058Z (8 months ago)
- Topics: deep-learning, forecasting, machine-learning, statistics, timeseries
- Language: HTML
- Homepage: https://marcozanotti.shinyapps.io/ForecastApp/
- Size: 3.84 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 8
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Metadata Files:
- Readme: README.md
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README
# Forecast App
The **Forecast App** is a comprehensive tool designed to guide users
through the entire forecasting workflow, from raw data to scenario analysis.
It is tailored for both beginners and experienced practitioners, allowing the
exploration, modeling, and explanation of time series data without requiring
advanced knowledge of forecasting techniques.
The app is organized into four main sections —**Data**, **Analyze**,
**Features**, and **Forecast**— which collectively enable users to:
- Upload and explore time series data
- Detect and handle missing values and anomalies
- Transform and preprocess data for improved forecasting performance
- Create and select relevant features, both internal and external
- Fit and optimize a wide range of forecasting models, including classical,
machine learning, deep learning, and ensemble approaches
- Evaluate, compare, and explain the models’ predictions
- Generate probabilistic forecasts and business-oriented scenarios
The app provides great flexibility in analysis: interactive visualizations,
configurable model parameters, and multiple options for evaluation and
explanation allow users to tailor the process to their specific needs.
You can access the stable version at [Forecast App](https://marcozanotti.shinyapps.io/ForecastApp/).
Follow the [user guide](https://marcozanotti.github.io/tsforecasting-dashboard/manual/forecastapp-manual.html)
to leverage the full potential of the Forecast App to obtain accurate
forecasts, understand model behavior, and explore different scenarios for
informed decision-making.
Feel free to share the Forecast App on LinkedIn if you find it useful and
remember to tag [me](https://www.linkedin.com/in/marco-zanotti-a6a978124/)!
If you find bugs or have suggestions for improvements, please open an issue on
[GitHub](https://github.com/marcozanotti/tsforecasting-dashboard/issues).
If you are interested in who I am and what I do, visit my
[website](https://marcozanotti.netlify.app/).
The [source code](https://github.com/marcozanotti/tsforecasting-dashboard) of
the Forecast App is available on GitHub under the MIT license.