Python-ML-model-Project

First ML model Project based on sklearn and using CSV file from Kaggle on World Happiness report of 2019. This model used basic libraries of python like pandas, numpy seaborn and matplot to visualise and plot variables of the dataset. I made the model by simply train and test method and then checked the accuracy by linear regression which was coming as 56%. Although, 56% is a poor score and that is why I implemented this same model over other algorithms as well - I used random forest and decison tree to imporve my model and I achieved it as well. By using these two I was able to have easy 81% of accuracy in my linear regression score. The project containing these two algos is in the next repository. The report of this project has been attateched as well.