https://github.com/rohitinu6/calgary-crime-data-analysis
This project analyzes Calgary's crime data and utilizes neural networks to predict future crime trends.
https://github.com/rohitinu6/calgary-crime-data-analysis
crime-analysis crime-data crime-prediction data-analytics data-science eda machine-learning machine-learning-algorithms neural-networks python visualization
Last synced: 8 months ago
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This project analyzes Calgary's crime data and utilizes neural networks to predict future crime trends.
- Host: GitHub
- URL: https://github.com/rohitinu6/calgary-crime-data-analysis
- Owner: rohitinu6
- Created: 2024-12-19T02:21:39.000Z (10 months ago)
- Default Branch: main
- Last Pushed: 2025-02-06T03:14:11.000Z (8 months ago)
- Last Synced: 2025-02-06T04:23:06.947Z (8 months ago)
- Topics: crime-analysis, crime-data, crime-prediction, data-analytics, data-science, eda, machine-learning, machine-learning-algorithms, neural-networks, python, visualization
- Language: Jupyter Notebook
- Homepage:
- Size: 1.31 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Calgary Crime Data Analysis and Neural Network Prediction
## 📌 Project Overview
This project analyzes Calgary's crime data and utilizes neural networks to predict future crime trends. It involves data preprocessing, visualization, and predictive modeling to assist law enforcement and policymakers in crime prevention.
## 🚀 Features
- Data cleaning and exploratory data analysis (EDA)
- Crime trend visualization and pattern recognition
- Implementation of machine learning and neural network models
- Model evaluation and comparison
- Crime prediction for better decision-making
## 🛠 Tech Stack
- Python
- Pandas, NumPy
- Scikit-learn, TensorFlow/Keras
- Matplotlib, Seaborn
- Jupyter Notebook
## 📂 Dataset
The dataset contains historical crime records, including:
- **Crime Type**
- **Location**
- **Date & Time**
- **Severity**
- **Reported Cases**
## 📊 Machine Learning Models Used
- Logistic Regression
- Random Forest Classifier
- Neural Networks (Deep Learning)
- Time Series Forecasting Models
## 🔥 Results
The models are evaluated using accuracy, precision, recall, and F1-score. The neural network model provides predictive insights into crime patterns.
## 📁 Repository Structure
```
📂 Calgary-Crime-Data-Analysis
│-- 📁 data (Dataset & processed data)
│-- 📁 notebooks (Jupyter Notebooks)
│-- 📁 models (Trained models)
│-- 📁 images (Code and Results Screenshots)
│-- 📄 README.md (Project documentation)
```
## 🖼 Code and Results
Include images of code and results in the `images` folder. Example:
## 📜 How to Run the Project
1. Clone the repository:
```bash
git clone https://github.com/rohitinu6/Calgary-Crime-Data-Analysis.git
```
2. Navigate to the project folder:
```bash
cd Calgary-Crime-Data-Analysis
```
3. Install dependencies:
```bash
pip install -r requirements.txt
```
4. Run the Jupyter Notebook or Python scripts to train and test models.
## 🔗 Links
- **GitHub Repository:** [Calgary Crime Data Analysis](https://github.com/rohitinu6/Calgary-Crime-Data-Analysis.git)
- **Portfolio:** [Rohit Dubey](https://tinyurl.com/dubeyrohit)
- **GitHub Profile:** [rohitinu6](https://github.com/rohitinu6)
- **LinkedIn:** [Rohit Dubey](https://www.linkedin.com/in/rohit-dubey-d/)
- **Twitter/X:** [@rohitdubey003](https://x.com/rohitdubey003)
## 🔖 Tags
`Machine Learning` `Crime Prediction` `Data Analysis` `Neural Networks` `Python` `EDA`
## 📝 License
This project is licensed under the [MIT License](https://opensource.org/licenses/MIT).
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💡 **For any queries or collaboration opportunities, feel free to connect!** 🚀