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🌦️ Build an end-to-end pipeline for collecting, storing, and predicting weather data using robust scraping and machine learning techniques.

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🌀️ WeatherForecast - Simple Weather Predictions Made Easy

πŸ“₯ Download Now

Download WeatherForecast

πŸ“– About This Project

WeatherForecast is an end-to-end time series forecasting project. It allows you to compare different methods for predicting weather patterns using real data. We explore three approaches: ARIMA, N-BEATS, and a custom PyTorch Long Short-Term Memory (LSTM) model. This project makes it easier for you to understand how different models can forecast weather data.

πŸš€ Getting Started

To get started with WeatherForecast, follow these simple steps:

  1. System Requirements

    • Windows, macOS, or Linux operating system
    • Python 3.7 or newer installed on your machine
    • Basic internet connection for data fetching
  2. Downloading the Application Visit this page to download: WeatherForecast Releases.

  3. Installation Steps

    • Once you reach the Releases page, you'll see various files.
    • Choose the latest version of the application based on your operating system.
    • Download the file and save it to a location you can easily access, such as your Desktop or Downloads folder.

πŸ“Š Features

  • Multiple Models: Use ARIMA, N-BEATS, or LSTM for forecasting.
  • Data Analysis Tools: Integrated tools to analyze weather data effectively.
  • User-Friendly Interface: Designed for people at all skill levels.
  • Customization Options: Adjust parameters to see their impact on forecasts.

πŸŽ“ How to Use WeatherForecast

  1. Open the Application

    • Locate the downloaded file on your computer.
    • Double-click the file to run it.
  2. Select Your Model

    • On the main screen, choose which model you want to use for forecasting: ARIMA, N-BEATS, or LSTM.
  3. Input Your Data

    • You can either upload a dataset of weather data or let the application scrape data from available online sources.
  4. Run Forecasting

    • Click on the "Forecast" button to generate predictions based on your selected model.
  5. View Results

    • After a moment, the application will display the forecasted weather patterns along with visual graphs.
  6. Save Your Predictions

    • You can easily save the results for future reference.

πŸ”§ Troubleshooting

If you experience issues, consider the following:

  • Ensure you are using the correct version of Python.
  • Make sure all dependencies are installed, which the application may prompt you to do.
  • Check your internet connection if you are fetching online data.

πŸ’¬ Community Support

If you have questions or need help, feel free to reach out to our community. Check the Issues section of the repository or visit our support page. We value your input and are here to help.

πŸ”— Additional Resources

For more information, explore the following topics:

πŸ“‹ Download & Install

To start using WeatherForecast, visit this page to download: WeatherForecast Releases. Follow the instructions above to install and run your application.

Explore the possibilities of time series forecasting today!

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