Overview This machine learning project aims to predict crime rates in Chicago using the Prophet forecasting tool. By leveraging historical crime data, the model forecasts future crime rates, providing valuable insights for law enforcement and city planning.
Table of Contents
About the Project
Data
Installation
Usage
Results
About the Project
Describe your project here. Discuss the motivation, objectives, and any specific challenges or goals you aimed to address. Highlight the significance of predicting crime rates in Chicago and how it contributes to public safety and urban planning.
Data
Explain the data used in the project. Provide information on the dataset, its source, and any preprocessing steps performed. If possible, include a sample of the dataset to give users an idea of its structure.
Installation
Provide instructions on how to install the required dependencies and set up the project environment. This may include Python packages, libraries, or any other tools necessary to run the code successfully.
pip install -r requirements.txt
Usage
Explain how users can run and interact with the project. Include examples of command-line usage, input formats, and any configuration settings. If applicable, provide sample code snippets to demonstrate key functionalities.
python crime_prediction.py
Results
Share the key findings and results of your crime rate predictions. Include visualizations, graphs, or any other representations that help communicate the outcomes of your machine learning model. Discuss any insights gained and potential applications.