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🔴 Project Title : Student Stress Level Detection
🔴 Aim : This project aims to predict student stress levels based on study load, academic performance and other stuff.
🔴 Dataset : https://www.kaggle.com/datasets/samyakb/student-stress-factors/data
🔴 Approach : Try to use 3-4 algorithms to implement the models and compare all the algorithms to find out the best fitted algorithm for the model by checking the accuracy scores. Also do not forget to do a exploratory data analysis before creating any model.
📍 Follow the Guidelines to Contribute in the Project :
You need to create a separate folder named as the Project Title.
Inside that folder, there will be four main components.
Images - To store the required images.
Dataset - To store the dataset or, information/source about the dataset.
Model - To store the machine learning model you've created using the dataset.
requirements.txt - This file will contain the required packages/libraries to run the project in other machines.
Inside the Model folder, the README.md file must be filled up properly, with proper visualizations and conclusions.
🔴🟡 Points to Note :
The issues will be assigned on a first come first serve basis, 1 Issue == 1 PR.
"Issue Title" and "PR Title should be the same. Include issue number along with it.
Follow Contributing Guidelines & Code of Conduct before start Contributing.
✅ To be Mentioned while taking the issue :
Full name :
GitHub Profile Link :
Participant ID (If not, then put NA) :
Approach for this Project :
What is your participant role? (Mention the Open Source Program name. Eg. HRSoC, GSSoC, GSOC etc.)
Happy Contributing 🚀
All the best. Enjoy your open source journey ahead. 😎
The text was updated successfully, but these errors were encountered:
Approach for this Project: I will do EDA first then data cleaning and data transformation if needed. After that, I will split data sets into training and testing sets. Then will use scaling and test with models like SVR, Decision Tree, Random Forest, and Gradient Boost and find a good model with high R2 and less MAE.
ML-Crate Repository (Proposing new issue)
🔴 Project Title : Student Stress Level Detection
🔴 Aim : This project aims to predict student stress levels based on study load, academic performance and other stuff.
🔴 Dataset : https://www.kaggle.com/datasets/samyakb/student-stress-factors/data
🔴 Approach : Try to use 3-4 algorithms to implement the models and compare all the algorithms to find out the best fitted algorithm for the model by checking the accuracy scores. Also do not forget to do a exploratory data analysis before creating any model.
📍 Follow the Guidelines to Contribute in the Project :
requirements.txt
- This file will contain the required packages/libraries to run the project in other machines.Model
folder, theREADME.md
file must be filled up properly, with proper visualizations and conclusions.🔴🟡 Points to Note :
✅ To be Mentioned while taking the issue :
Happy Contributing 🚀
All the best. Enjoy your open source journey ahead. 😎
The text was updated successfully, but these errors were encountered: