Unemployment Rate Predict Model

A comprehensive machine learning system for predicting unemployment rates in Canada using multiple economic indicators. This project combines traditional statistical methods with modern deep learning approaches to provide accurate short-term unemployment rate forecasts.

📖 Project Description

For detailed information about the project's technology stack, methodology, and architecture, please see our comprehensive Project Description.

Installing Dependencies

Install the required Python packages using the provided requirement.txt file

pip install -r requirements.txt

Running the experiment

Execute Training process

python Training.py

Execute Test process

python Test.py

File Structure

├── README.md
├── datasets/
│   ├── filtered_data/
│   │   └── [Filtered datasets]
│   └── raw-data/
│       └── [Raw datasets downloaded from Statistics Canada]
├── Test.py (Testing and validations)
├── Training.py (Training LSTM and LR models)
├── models/
│   ├── data_preproces_piplines/
│   │   └── [Scripts for data cleaning and formatting]
│   ├── [saved training and validation losses during training process of LSTM model]
│   └── [saved model files]
└── requirements.txt

👥 Credits

This project was developed collaboratively by:

• Yunze(Figo) Li
• Qiwen(Kyra) Jiao
• Chenrui(Eric) Hao

Please replace the placeholder names and GitHub usernames with the actual contributors to this project.