Welcome to Job Mailer a personalized job recommendation system ! This project leverages a powerful combination of data scraping, cutting-edge machine learning techniques, a user-friendly Streamlit application, and seamless cloud deployment to offer you a state-of-the-art job recommendation experience.

Are you tired of shifting through countless job listings, unsure if they're the right fit for you? Job Mailer is here to help you with your job search process, making it more efficient and personalized.

1. Data Scraping: We gather job data from Glassdoor, one of the leading job search platforms. The data scraping process ensures that we have access to the latest and most relevant job listings.

2. Data Preprocessing: The collected job data can be messy and unstructured. Our system includes custom data preprocessing components to clean and format the data, making it ready for machine learning.

3. Machine Learning Algorithms: We employ advanced machine learning algorithms that take your preferences and skills into account to generate personalized job recommendations. Say goodbye to generic job listings!

4. Streamlit Application: We've developed a user-friendly Streamlit application that provides an intuitive and interactive interface for you to explore and interact with the job recommendations. With Streamlit, you can easily customize your preferences and see real-time updates to your job matches.

5. Cloud Deployment: To ensure accessibility and scalability, our system is deployed on the cloud. You can access your personalized job recommendations from anywhere, anytime, without worrying about system limitations.

Follow these steps to get started with Job Mailer:

1. Clone this repository to your local machine:

   git clone https://github.com/your-username/JobMailer.git
   

2. Install the required dependencies:

   pip install -r requirements.txt
   

3. Run the Streamlit application:

   streamlit run __init__.py
   

4. Customize your preferences, explore job recommendations, and start your job search journey!

• Python
• Scikit-Learn
• Streamlit
• Selenium
• Spacy
• nltk
• pandas
• numpy

We welcome contributions to enhance and expand the functionality of our Job Recommendation System. If you're interested in contributing, here are few additional features that I'm planning to include in the project:

• User Authentication
• Email Notification
• Interview Tips
• Resume Enhancement Tips
• Adding more data and preferred Job Roles

Happy job hunting! 🚀🌟