CK Logo
Bootcamps
Projects
Post main image

Regression Analysis on Life Expectancy

Models used: Linear, Ridge, LASSO, Polynomial Regression

User profile image
attends Metis
2 months ago
#8 Project of March

In this project, I would like to predict the life expectancy of people in a country, and looked for data on the following aspects (features): · Birth Rate · Cancer Rate · Dengue Cases · Environmental Performance Index (EPI) · Gross Domestic Product (GDP) · Health Expenditure · Heart Disease Rate · Population · Area · Population Density · Stroke Rate I will use these data related to life expectancy to evaluate the following models: Linear, Ridge, LASSO, and Polynomial Regression. Here are some interesting insights: 1. Japan has the highest life expectancy (83.7 years). Central African Republic (49.5 years) and many countries in the African continent are at the bottom of scale. Singapore is ranked #5 (82.7 years). 2. Take good care of the environment. It has the largest coefficient (impact) on the country’s life expectancy. More details on this project: Medium: https://towardsdatascience.com/regression-analysis-on-life-expectancy-6914775a77e2 Coil: https://coil.com/p/jnyh/Regression-Analysis-on-Life-Expectancy/4urnznQhC Github: https://github.com/JNYH/Project-Luther

Video demo
Screenshots
Project screenshot 1
Project screenshot 2
Project screenshot 3
11
36

Skip straight to final coding interviews with
Remote Companies!

CK Projects Rewards

1. Get feedback on your portfolio projects from fellow techies and makers.

2. Free 3 months subscription to Crash to pitch top companies.

3. Access Career Karma Hiring Assessment powered by Triplebyte to introduce top bootcamp students to remote friendly tech companies.

4. Portfolio Projects Masterclass Workshops.

Top Makers

Most active posts

Top projects

Wow 😮
It seems like no one added any projects during the past week...