AIResume Helper Documentation Overview

AIResume Helper is an AI-powered tool designed to assist job seekers in optimizing their resumes for a better job application process. It utilizes advanced algorithms to offer personalized enhancements and feedback.

Tutorial: Getting Started with AIResume Helper

Objective: Guide new users through the initial setup and basic usage of AIResume Helper.

1. Installation Requirements: Ensure Python 3.8+ and Pip are installed.
2. Setting Up: Clone the AIResume-Helper repository and install dependencies via Pip.
3. First Use: Launch AIResume Helper using Streamlit and navigate to the provided localhost URL in your browser.

For a step-by-step walkthrough, visit our Getting Started Tutorial.

How-to Guide: Enhancing Your Resume

Objective: Provide users with instructions on specific tasks to improve their resumes.

• Adding Skills: How to interpret skill recommendations and include them in your resume.
• Choosing Courses: Steps to add suggested courses and certifications to your profile.
• Customizing Your Resume: Selecting and applying different templates for a professional look.

Explanation: Understanding AIResume Helper

Objective: Offer insights into how AIResume Helper works and the benefits it provides.

• Resume Parsing: Explains the technology behind extracting information from resumes.
• Skill and Course Recommendations: Delves into how AIResume Helper analyzes your resume and suggests improvements.

Gain a deeper understanding of AIResume Helper's features here.

Reference: Technical Documentation

Objective: Present detailed technical information and commands for advanced users.

• Installation Commands:

  git clone https://github.com/Nirothor/AIResume-Helper.git
  cd AIResume-Helper
  pip install -r requirements.txt
  
  streamlit run app.py
  
  

Contributing

We welcome contributions to AIResume Helper! If you have suggestions for improvements or bug fixes, please open an issue or submit a pull request.

License

See the LICENSE file for more details.

Acknowledgments

Special thanks to Streamlit for making interactive web app development accessible to data scientists and developers.

Thanks to all contributors and users of AIResume Helper for your support and feedback.

Contact

If you have any questions or comments about AIResume Helper, please feel free to open an issue.