From growing up in the heart of Silicon Valley, I have always wondered what was the factors that play a role in Suicide. There have been a plethora of suicide clusters from my High School in Palo Alto. This project seeks to explore the underlying factors. We will use a sample of 44,000 gather data from 141 different Countries, between the 80's to 2016. We would like to make a Machine Learning algorithm where we can train our AI to learn & improve from experience. Thus, we would want to predict the amount of suicides numbers in a certain demographic.
Author: Jarar Zaidi
Date: 6/8/2020
Medium Link to project: https://medium.com/@jararzaidi/the-suicide-crisis-in-data-7025f8551ca8
This repository is organized as follows:
The Suicide Crisis in Data.ipynb - the jupyter Notebook (.ipynb) version of project
The Suicide Crisis in Data.py - the Python (.py) version of this Python project using Seaborn,Pandas,Numpy, Matplolib
who_suicide_statistics.csv - Original dataset used from Kaggle.com in CSV (.csv) format
who_suicide_statistics.xlsx -Dataset from Kaggle.com in Excel Format(.xlsx), must be converted to Excel format inorder to be used for Tableau Public Data Visualization Software
Suicide In Numbers.PDF
- Used Data Tableau Public Software to create a Data Visulaization of the Topics discussed
from the Python Notebook
Table of Contents: 1.Introduction 2.Data Wrangling 3.Exploratory Data Analysis 4.Machine Learning + Predictive Analytics 5.Conclusions 6.References