AI Forecasting App - Shiny Contest Submission

AI Forecasting App

Authors: Soumyadipta Das

Abstract: The AI Forecasting Tool, built on the R Shiny architecture, offers a user-friendly platform for data analysis. R Shiny enables the creation of interactive applications without extensive web development skills. Users can upload, edit, and visualize data seamlessly. The tool provides various models for tailored predictions and forecasts, with easy extraction of results. Additionally, it includes an interactive AI component for discussions and insights, making it a valuable asset for data-driven decision-making.

Full Description: The AI Forecasting Tool, based on the R Shiny architecture, provides a comprehensive and user-friendly platform for all your data analysis needs. R Shiny, a web application framework for R, allows for the creation of interactive and visually appealing applications without requiring extensive web development skills. Leveraging this powerful framework, users can seamlessly upload their data, make necessary edits, and visualize the information in an intuitive manner. The tool offers a variety of models to choose from, allowing for tailored predictions and forecasts to suit specific requirements. Once the forecasting process is complete, users can easily extract the results for further use. Moreover, the tool includes an interactive AI component that enables discussions on multiple topics, providing valuable insights and guidance throughout the analysis process. This combination of advanced functionality, ease of use, and interactive features makes the AI Forecasting Tool an essential asset for data-driven decision-making.

The top features are as follows -

  • Upload your data
  • Edit and visualize your data
  • Select desired model
  • Predict and forecast
  • Extract the results
  • Discuss multiple topics with AI

Shiny app: https://soumyadipta-das-stat.shinyapps.io/forecasting_tool_new/
Repo: GitHub - Soumyadipta2020/forecasting_tool: Forecasting tool for Time-Series and Non-time series data

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