APD Crime Data Analysis

This repository contains an early-stage machine learning project that explores Atlanta Police Department (APD) crime data. The project aims to analyze crime patterns, trends, and correlations using various data science Python libraries and models from Google's Model Garden.

Overview

The project leverages Python and popular data science libraries such as Pandas, Matplotlib, Seaborn, and Scikit-learn to perform data preprocessing, exploratory data analysis (EDA), model training, and evaluation. Additionally, it explores models from Google's Model Garden to analyze crime data and extract insights.

Project Structure

• data: Directory containing the APD crime data CSV file(s).
• notebooks: Jupyter notebooks for data analysis, EDA, and model experimentation.
• models: Scripts or notebooks for training and evaluating machine learning models.
• README.md: Main documentation file providing an overview of the project.
• requirements.txt: File listing Python dependencies for the project.

Getting Started

To get started with the project, follow these steps:

1. Clone the repository:

   git clone https://github.com/your-username/apd-crime-data-analysis.git
   cd apd-crime-data-analysis

2. Set up a Python virtual environment and install dependencies:

   python3 -m venv venv
   source venv/bin/activate  # On macOS and Linux
   pip install -r requirements.txt

3. Explore the data and notebooks in the notebooks directory to understand the analysis workflow and experiments conducted.

4. Run the provided scripts or notebooks to preprocess the data, perform EDA, train machine learning models, and evaluate model performance.

Data

The APD crime data used in this project is sourced from [insert source link]. The dataset contains information about various crimes reported in Atlanta, including crime type, location, date, time, and other relevant attributes.

Models

The project explores various machine learning models available in Google's Model Garden, including [list some models]. These models are used to analyze the APD crime data and extract meaningful insights.

Contributing

Contributions to the project are welcome! If you have any ideas, suggestions, or improvements, feel free to open an issue or submit a pull request.

License

[Insert license information]