-
Notifications
You must be signed in to change notification settings - Fork 54
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Covid-19 Prediction using ML/DL techniques #142
Comments
Congratulations, @jeet-Abhi123! 🎉 Thank you for creating your issue. Your contribution is greatly appreciated and we look forward to working with you to resolve the issue. Keep up the great work! We will promptly review your changes and offer feedback. Keep up the excellent work! Kindly remember to check our contributing guidelines |
@SrijanShovit May I know the reason why you have closed this issue? |
You really think we need Covid 19 analysis now? Try exploring the repo first, what's going; which issues have been closed. |
@SrijanShovit I am not talking about just Covid-19 analysis. |
Your current comment does not align with this: 🔴 Project Title : Covid-19 prediction using ML/DL 🔴 Aim : This dataset was collected in the initial phases of covid-19 during march and april 2020. The aim of the project is to predict a person is covid-19 +ve or not with minimum possible symtoms like fever, cough, age_above_60, sore_throat etc Still you can chose some idea on the line of lung/ bronchiole related disease or similar kind of virus. But would need some other dataset generic to these symptoms. |
Health Learning Repository (Proposing new issue)
🔴 Project Title : Covid-19 prediction using ML/DL
🔴 Aim : This dataset was collected in the initial phases of covid-19 during march and april 2020. The aim of the project is to predict a person is covid-19 +ve or not with minimum possible symtoms like fever, cough, age_above_60, sore_throat etc
🔴 Dataset : Taken from research paper and provided by Israeli Ministry of Health https://www.nature.com/articles/s41746-020-00372-6
🔴 Approach : First will perform EDA on the dataset, and then perform feature engineering on the columns. Will experiment with multiple models like ANN, Gradient Boosting , Decision trees etc. After will perform hyperparameter tuning through KerasTuner and will plot the results graph.
Kindly assign me the issue under the label of GSSoC'24.
The text was updated successfully, but these errors were encountered: