PISA Performance Scores Analysis

[abhisheks008]

ML-Crate Repository (Proposing new issue)

:red_circle: Project Title : PISA Performance Scores Analysis :red_circle: Aim : The aim of this project is to analyze the dataset using machine learning models. :red_circle: Dataset : https://www.kaggle.com/datasets/thedevastator/pisa-performance-scores-by-country :red_circle: 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.

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📍 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.

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:red_circle::yellow_circle: 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.

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:white_check_mark: 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.)

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Happy Contributing 🚀

All the best. Enjoy your open source journey ahead. 😎

[raysofani]

Hi @abhisheks008 , I would like to take up this issue!! Full name : Aniket Ray GitHub Profile Link : https://github.com/raysofani Participant ID (If not, then put NA) : NA Approach for this Project :

EDA Processing Feature engineering Use 3-4 algorithm to Analyse and do the required Prediction. Will use Regression algorithm like linear regression, Decision Tree, Random Forest and XGboost for improved accuracy. finally based on the complexity of dataset best suited algoithm will be used. What is your participant role? IWOC 2.0

[abhisheks008]

Complete your previous issue first @raysofani

[mariam7084]

Hi @abhisheks008 I would like to take this issue.

Full name : Mariam GitHub Profile Link : github.com/mariam7084 Participant ID : NA Approach for this Project : perform EDA and visualize the results What is your participant role? JWoC 2024

[abhisheks008]

Assigned @mariam7084