Feature request-Crop Yeild Prediction

[Shy029]

For a Crop Yield Prediction feature in ML Nexus, I propose to create an end-to-end solution that predicts agricultural crop yields based on historical and environmental data. The pipeline includes data preprocessing (handling missing values, encoding categorical variables, and outlier removal), feature engineering, and training models like Linear Regression, Decision Trees, or Random Forest for accurate yield predictions. The feature would also support dataset uploads for customized, region-specific predictions, with evaluation metrics (e.g., Mean Squared Error) built-in for model assessment. This tool will enhance agricultural planning by offering reliable, data-driven insights directly within ML Nexus.

please assign this to me.

[github-actions]

Thanks for creating the issue in ML-Nexus!🎉
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[github-actions]

Hey @Shy029, can you share the progress of this project?

[Shy029]

It will be completed at the end of the day.

[github-actions]

Hello @Shy029! Your issue #703 has been closed. Thank you for your contribution!