krupadivakar Goto Github PK

android-project

bigdataanalysis-crimedata

Big data analysis using spark on famous kaggle data set - Chicago Crime. Visualizations using python libraries have also been used for better visual understanding of the analysis

chicago-crime-data-analysis

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

computer-network-laboratory

We have transferred this Repository to the mentioned link. Please Visit that for further updates

database_connection_php

dbms_project-inventory-

depressiondetection

django-tutorials

Source code for my free YouTube series on the Django web framework for Python.

doctor_patient-project

gitsession

heart-disease-classifier-web-app

Heart disease classifier web app

medium-tutorials

pes_final_year_project

pharma-php

predpol---crime-analysis

Crimes have been severely increased in past few years, the Problem Statement includes analysis of crimes with different perspectives including utmost attributes possible and predicting via the study of nature of crimes committed. The problem statement is described to initially predict the crime-type based on location and time. We worked on data about historical crimes in California. We had close to 13,000 records of crimes with data on the date and time of the crime, its location, and its type. Common types of crime include theft, criminal damage, criminal trespass, and assault. This project took on the task of predicting the type of crime that was committed given a police report in two ways one according to time that is when crime took place and another is location that is where crime took place. From a small number of overly detailed features, in time it will give the detail that at which time slot which crime is maximum and in location it will tell at which place which type of crime is maximum. They then trained various diagram based models (Graphs and Pie charts) to classify crimes by type using the generated features. Finally, they tested the performance of their models on testing data. They conclude that predicting the type of crimes committed by time and location alone is quite difficult, but that the feature engineering greatly increases predictive power. Predictions will be made to provide local authorities with an upper hand on crime and help them plan a better strategy to tackle the same.

react-projects

sample

sf-crime-data-analysis-and-modeling

Spatial and Time Series Analysis of San Francisco Crimes

spoon-knife

This repo is for demonstration purposes only.

testgit

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