Some self-discovery projects related to data science and machine learning
-
Updated
May 9, 2017 - Jupyter Notebook
Some self-discovery projects related to data science and machine learning
Investigating the problem of slowing police response rates and evaluating if a practical software solution can be produced to predict and provide informed decisions to ground officers
A simple crime statistics app, used to get UK crime data based on location, crime categories and dates.
Dades delinqüencials Catalunya segons Àrees Bàsiques Policials
🔔 Analysis of Vancouver crimes recorded from 2013 to 2019
Regression and Statistical analysis of crimes in Chicago from 2015 until 2020.
This project aims to understand the algorithmic bias in the corrections system through analyzing the COMPAS dataset.
Research Project I completed under Dr Vinti Agrawal at BITS Pilani.
This project analyzes hate crimes reported in the NYPD using data from a Kaggle dataset. It explores temporal and spatial patterns, offense types, bias motivations, and arrest trends. The analysis involves data cleaning, preprocessing, and visualization to reveal insights into crime trends and geographical concentrations.
Crime prediction
Final Project for a computer Science course.
An android application which allows you to see crimes in a certain area and plots the data on a map.
Analysis of crime data by U.S. Census Bureau block groups within the city of San Diego.
Python code that provides a tool for analyzing and visualizing crime data
A BFO and CCO conformant ontology of criminal acts
An interactive map that shows crime information and statistics in the UK
The code I wrote to produce the visualizations on my blog article about a Los Angeles crime dataset. I have provided a link to the article.
Add a description, image, and links to the crime-data topic page so that developers can more easily learn about it.
To associate your repository with the crime-data topic, visit your repo's landing page and select "manage topics."