RemotePathy

RemotePathy is a platform designed to bridge the gap between job seekers and remote job opportunities. It offers a tailored job recommendation system that suggests relevant job listings based on a user's resume, location, and other preferences. Our mission is to streamline the remote job search experience for users, particularly recent graduates and professionals seeking flexible work environments.

Features

• Job Listings: Browse curated remote job opportunities from various industries.
• Resume Upload: Add your resume to receive personalized job recommendations.
• Job Recommendation System: Uses AI and ML algorithms to suggest jobs based on your skills, experience, location, and salary preferences.
• Authentication System: Secure login, signup, and profile management for users.
• Job Search Filters: Filter job listings by industry, location, salary range, and more.
• Third-Party API Integration: Aggregates remote job postings from other websites using their APIs.
• Resources Section: A repository of guides, tips, and articles to help users improve their remote work experience.

Technologies

• Backend: Django, Django REST Framework (DRF)
• Frontend: React.js
• Database: MySQL
• Machine Learning: Python, Scikit-learn (for job recommendation system)
• APIs: Integration with third-party job platforms

Setup Instructions

Prerequisites

• Python 3.x
• Node.js and npm
• MySQL
• Virtual Environment (optional)

Backend Setup

1. Clone the repository:

   git clone https://github.com/Blessman-Newton/remotepathy.git
   cd remote-path

2. Create a virtual environment:

   python -m venv env
   source env/bin/activate  # For Windows, use `env\Scripts\activate`

3. Install dependencies:

   pip install -r requirements.txt

4. Configure MySQL database:

   • Set up a MySQL database and update the DATABASES setting in settings.py with your credentials.

5. Run database migrations:

   python manage.py migrate

6. Create a superuser:

   python manage.py createsuperuser

7. Start the Django server:

   python manage.py runserver

Frontend Setup

1. Navigate to the frontend directory:

   cd frontend

2. Install frontend dependencies:

   npm install

3. Start the React development server:

   npm start

Machine Learning Setup

1. Navigate to the ml directory:

   cd ml

2. Install ML dependencies:

   pip install -r requirements.txt

3. Run the ML scripts to train and evaluate the job recommendation model.

Authors

Blessman Newton - GitHub Lead Developer, Backend, Machine Learning Systems and API Integrations Specialist

Contributing

Contributions are welcome! To get started:

1. Fork the repository.
2. Create a new branch (git checkout -b feature-branch).
3. Make your changes and commit them (git commit -m "Add a new feature").
4. Push to the branch (git push origin feature-branch).
5. Open a pull request.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contact

For any inquiries or support, please email us at blessmannewton0@gmail.com.