Suicide Rate Prediction with Machine Learning

Final Project for Machine Learning & Data Analysis Course - University of New Haven

Introduction:

         Suicide is a serious public health problem. The World Health Organization (WHO) estimates that every year close to 800 000 people take their own life, which is one person every 40 seconds and there are many more people who attempt suicide. Suicide occurs throughout the lifespan and was the second leading cause of death among 15-29-year-olds globally in 2016.

         The objective of this project is to predict the suicide rates using Machine Learning algorithms and to analyzing significant patterns features that result in increase of suicide rates globally. This project is done in the Google Collaboratory.

Project Notebook:

         This Jupyter Notebbok has the code, visualizaed plot, model execution, model results and computed two statistical tests of this project.

Project Presentation:

         The project presentation has few slides about the inital stages of the project development.

Project Report:

         The project report has the detailed description about the working and execution of the project along with the explanation of the code.