https://github.com/nysportsfan/Gun-Violence-in-the-US

This repository contains all the relevant files for my first capstone project as part of the Springboard Data Science Career Track.
https://github.com/nysportsfan/Gun-Violence-in-the-US

data-analysis data-science data-visualization machine-learning python3 statistics

Last synced: 3 months ago
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This repository contains all the relevant files for my first capstone project as part of the Springboard Data Science Career Track.

• Host: GitHub
• URL: https://github.com/nysportsfan/Gun-Violence-in-the-US
• Owner: nysportsfan
• Created: 2018-07-04T19:57:58.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2018-12-03T18:39:56.000Z (almost 6 years ago)
• Last Synced: 2024-04-30T15:32:34.348Z (6 months ago)
• Topics: data-analysis, data-science, data-visualization, machine-learning, python3, statistics
• Language: Jupyter Notebook
• Homepage:
• Size: 12.6 MB
• Stars: 1
• Watchers: 1
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

• awesome-springboard-capstones - GitHub

README

        
# Capstone-Project-1

Welcome to my very first Capstone Project: Analyzing Gun Violence in the US

Here I have attached all the relevant components for the project:

1) Data Wrangling - Collecting, cleaning and transforming the data.

2) Exploratory Data Analysis - Using data visualization to investigate trends and tell a story.

(Note: Please open the EDA notebook with NBviewer to view the plotly visualizations)

3) Inferential Statistics - Observing the correlations between feature and response variables.

4) Machine Learning - Creating the machine learning models to predict the response variables.

5) Milestone Report - An update report half-way into the capstone project process.

6) Project Proposal - The proposal for the capstone project.

7) Final Presentation folder - A folder containing the final abstract report and the Powerpoint presentation slides.

8) Images folder - A folder containing the images (data visualization, pandas dataframes) used for the final presentation.

Enjoy browsing through my work and if you have any questions or suggestions, please do not hesitate to let me know.

I will be updating this project on and off to add improvements to the ML models, presentation, data visualization, etc. 

I can be reached via email: [email protected]

Thank you!

Update 1 (9/11/18): Dropped the incident_characteristics, mapped_primary, mapped_secondary columns due to data leakage.

Made edits to the Inferential Statistics, Machine Learning notebooks, Final Presentation slides and Final Abstract report.