Crime classification, analysis & prediction in Indore city

A Django Based Crime Visualization and ML Application

Association Rule Mining from Spatial Data for Crime Analysis

Crime analysis in R

R package for accessing data from the Crime Open Database

This project gives an overview of crime time analysis in New York City . We have created Python Jupyter notebooks for spatial analysis of different crime types in the city using Pandas, Numpy, Plotly and Leaflet packages. As a second part to this analysis, we worked on ARIMA model on R for predicting the crime counts across various localities in…

A selection of Shiny apps

[Data Science] Chicago Crime data analysis from 2001 to present.

Manhattan crime data visualization dashboard made with D3

Open crime data from US cities in a harmonised format

Tutorials for crime mapping in R

This Problem Data set of San Francisco Contains information about the crime in San Francisco, We are going to analyze the data, Visualize the data using folium maps for geographical understanding. In other words It is called Geo spatial Mapping. This Problem is the final assignment for Coursera and IBM's Data Visualization Course.

One stop download for year wise crime statistics in India.

Analyzing and forecasting crime in Mexico (Project done as part of a course at UChicago - Winter 2017)

Crime Trend and Fatalities Prediction in Nigeria

Analyse Los Angeles Crime rate between 2012 - 2016 using python pandas, numpy and matplot libraries

This repository contains jupyter notebook implementation for crime type prediction on the basis of spatial and temporal data available.

Seoul, South Korea : crime analysis

Crime analysis and visualization in the city of Boston. Utilizing Boston Police Department's dataset available at https://data.boston.gov/dataset/crime-incident-reports-august-2015-to-date-source-new-system . Project currently in progress

Crime and Criminal Analysis System integrating geospatial, temporal, and demographic analytics for predictive modeling of criminal activities. It employs machine learning for optimizing police resource allocation and incorporates real-time social media scraping for proactive crime detection.