We train Linear Regression, Neural Networks, and other machine learning models on data from the World Happiness Report to quantitatively define the main factors affecting humans’ subjective sense of happiness and thus develop a method to predict happiness.
-
Notifications
You must be signed in to change notification settings - Fork 0
We train Linear Regression, Neural Networks, and other machine learning models on data from the World Happiness Report to quantitatively define the main factors affecting humans’ subjective sense of happiness and thus develop a method to predict happiness.
MoemenGaafar/World-Happiness-Machine-Learning
Folders and files
Name | Name | Last commit message | Last commit date | |
---|---|---|---|---|
Repository files navigation
About
We train Linear Regression, Neural Networks, and other machine learning models on data from the World Happiness Report to quantitatively define the main factors affecting humans’ subjective sense of happiness and thus develop a method to predict happiness.
Topics
Resources
Stars
Watchers
Forks
Releases
No releases published
Packages 0
No packages published