Best Country to Live In 2024

[abhisheks008]

ML-Crate Repository (Proposing new issue)

🔴 Project Title : Best Country to Live In 2024
🔴 Aim : The aim of the project is to make an analysis model to find out the best country for living in 2024 based on the dataset.
🔴 Dataset : https://www.kaggle.com/datasets/rafsunahmad/best-country-to-live-in-2024
🔴 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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🔴🟡 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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✅ 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. 😎

[YADAVEESHU]

Name: eeshuyadav
Git: https://github.com/YADAVEESHU
PID: NA
Approach : I will develop maps to show the relationship between population density and happiness scores,to visualize geographic distributions of HDI and population data.Enhance model accuracy, especially for happiness score predictions,Initially use linear regression, then enhance the model for happiness score predictions using Random Forest Regressor,Assess model performance using metrics like MSE and R-squared.
Program: JWoC

[abhisheks008]

Assigned @YADAVEESHU

[professor1412]

Name: Kanhaiya yadav
Git: https://github.com/professor1412
please assign it to me.

[abhisheks008]

Name: Kanhaiya yadav Git: https://github.com/professor1412 please assign it to me.

Already assigned to someone.

[shivansh-2003]

Can You Please Assign this issue under SSOC. 2024 Season 3
Shivansh Mahajan
Github:- https://github.com/shivansh-2003
Participation ID:- NA
I will do EDA of the data set by various statistical methods like IQR , Study Distribution OF Feature and Correlation Matrix.
I would train the data in Various ML model to. arrive to the better Accuracy score. I would then feed the data for Feature engineering and then train it with different machine learning models KNN , Random forest , Decision Tree , SVM and Bossting Algorithms
. I am well versed with Machine Learning you can check out my linkedin :-https://www.linkedin.com/in/shivansh-mahajan-13227824a/ and Git repository .
can u assign me with this issue @abhisheks008
Participation Role:- SSOC Season 3

[abhisheks008]

Contributions will start from June 1, 2024. Till then please have some patience.

[Rithish5513U]

Full name : Rithish S
GitHub Profile Link : https://www.github.com/Rithish5513U
Participant ID (If not, then put NA) : NA
Approach for this Project :
I will perform data preprocessing technique and clean the data, then i will do EDA on the dataset followed by the data visualization and feature engineering process. Then I will be training models like SVM, Decision Tree, Random forest , etc and compare their accuracy. I will also use hyperparameter tuning methods to find best usage of models and cross validation methods if required.

What is your participant role - SSOC Season 3

[abhisheks008]

Implement 5-6 models for this project/dataset.

Assigned @Rithish5513U

[Rithish5513U]

@abhisheks008 I don't understand what to predict in the given dataset. I can just analyze the HDI for each country and Happiness of each country, I don't know for what prediction I should use ML algorithms. Is the visualization and explanation of EDA is enough or anything can I do with the dataset? Any suggestion or queries? Pls check the dataset and tell me what to do.

[abhisheks008]

@abhisheks008 I don't understand what to predict in the given dataset. I can just analyze the HDI for each country and Happiness of each country, I don't know for what prediction I should use ML algorithms. Is the visualization and explanation of EDA is enough or anything can I do with the dataset? Any suggestion or queries? Pls check the dataset and tell me what to do.

If this dataset is not feasible with the desired model implementation, you can find a new dataset with the same problem statement and post it here. I'll review it.