Crime Data Analysis Project

Overview

This project analyzes crime data from a CSV file containing information such as crime codes, locations, victim ages, and more. The goal is to build a predictive model that can analyze both text and numeric data to predict crime occurrences.

Project Structure

• data/: Contains the CSV file with crime data.
• crime_analysis.ipynb: Jupyter Notebook with the data analysis and model building code.
• requirements.txt: Python dependencies required for running the code.
• README.md: This file providing an overview of the project.

Dependencies

To run the code, you'll need the following dependencies:

• Python 3.x
• TensorFlow
• pandas
• scikit-learn
• matplotlib
• seaborn

You can install the dependencies using the command:

pip install -r requirements.txt

Usage

1. Clone the repository to your local machine:

git clone https://github.com/MuhammadTalha121/Crime_report_2020_to_present.git

2. Install the dependencies:

pip install -r requirements.txt

3. Run the Jupyter Notebook crime_analysis.ipynb to analyze the crime data and build the predictive model.

Contributors

• Muhammad-Talha-Team (Data Scientist)

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