https://github.com/salihfurkaan/world-happiness-report

An analysis on the world happiness report.
https://github.com/salihfurkaan/world-happiness-report

data-science gradient-boosting-regressor k-nearest-neighbors linear-regression machine-learning-algorithms world-happiness-report

Last synced: 9 months ago
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An analysis on the world happiness report.

• Host: GitHub
• URL: https://github.com/salihfurkaan/world-happiness-report
• Owner: salihfurkaan
• License: apache-2.0
• Created: 2023-09-23T12:34:02.000Z (about 2 years ago)
• Default Branch: main
• Last Pushed: 2023-10-04T18:32:07.000Z (about 2 years ago)
• Last Synced: 2024-12-28T05:16:28.606Z (10 months ago)
• Topics: data-science, gradient-boosting-regressor, k-nearest-neighbors, linear-regression, machine-learning-algorithms, world-happiness-report
• Language: Jupyter Notebook
• Homepage:
• Size: 1.88 MB
• Stars: 2
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# World Happiness Report

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An analysis on the world happiness report in 2015 and 2016.




Click  here  to see the dataset!

**Used Technologies**

- Python (Seaborn, Matplotlib, Pandas, Scikit-learn)

**Applied Machine Learning Algorithms:**

  - Linear Regression

  - K-Nearest-Neighbors 

  - Gradient Boosting Regressor

In this project, it is aimed to see what affects the happiness of a country and how it changes.