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@How-to-Train-Your-AI-Dragon

How to Train Your AI Dragon

Practice AI Dragon at Universiti Malaya (UM)
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Group Name: How to Train Your AI Dragon (Group 1)

Project Title: Revolutionizing HR Interview Processes with AI

🎓 Course Information

Course Code: WID3014
Course Name: Practical AI

🔍 Problem Statement

In today's competitive job market, HR departments face significant challenges:

  • Volume Overload: HR professionals spend countless hours screening hundreds of applications for each position
  • Consistency Issues: Manual screening can lead to inconsistent evaluation criteria across candidates
  • Time Constraints: The pressure to fill positions quickly can result in overlooking qualified candidates
  • Unconscious Bias: Human reviewers may inadvertently bring personal biases into the screening process
  • Resource Intensive: Traditional interview processes require significant time and human resources
  • Candidate Experience: Delayed responses and lack of feedback negatively impact candidate experience

Our AI-powered solution addresses these challenges by automating the initial screening process, ensuring fair evaluation, and significantly reducing the time-to-hire while maintaining high-quality candidate selection.

🎯 Our Solution

We're developing an intelligent HR filtering system that:

  • Automates initial candidate screening using advanced LLM technology
  • Provides consistent evaluation criteria across all applications
  • Reduces time-to-hire by up to 75%
  • Minimizes unconscious bias in the selection process
  • Improves candidate experience through quick feedback
  • Allows HR professionals to focus on high-value interactions

🤖 Key Features

  • Intelligent Resume Parsing: Extract and analyze key information from resumes
  • Automated Initial Screening: Use LLMs to evaluate candidate responses
  • Sentiment Analysis: Understand candidate communication style and soft skills
  • Custom Interview Generation: Create personalized interview questions based on job requirements
  • Bias Detection: Implement fairness checks in the filtering process
  • Performance Analytics: Track and analyze recruitment metrics

🛠️ Technologies & Tools

Python LLaMA Langchain Scikit-learn Gradio

🤝 How to Contribute

  1. Fork the repository
  2. Create your feature branch (git checkout -b feature/AmazingFeature)
  3. Commit your changes (git commit -m 'Add some AmazingFeature')
  4. Push to the branch (git push origin feature/AmazingFeature)
  5. Open a Pull Request

👥 Team Members

  • Poo Wei Chien
  • Tan Guo Dong
  • Goh Yi Xian
  • Tan Wei Ling
  • Cheok Xin Yu

Made with ❤️ by WID3014 Practical AI students

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    Automated Interview Filtering System

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    Python 0 MIT 0 0 1 Updated Jan 15, 2025
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