As a fresher actively looking for opportunities, I built this project to solve a real problem I personally faced — 👉 “How do I know if my resume matches a job description?”
This tool helps me (and others) evaluate resumes against job roles and improve them based on data-driven insights.
- 📊 Calculates how well a resume matches a job description
- 🔍 Identifies missing keywords
- 💡 Suggests improvements to increase chances of selection
- 📈 Visualizes match score
During my job search, I realized that many companies use ATS (Applicant Tracking Systems) to filter resumes.
As a fresher, it was difficult to understand:
- Why my resume gets rejected ❌
- What skills are missing 🤔
- How to tailor my resume for each job 🎯
So, I built this tool to:
- Analyze resumes like an ATS
- Improve my chances of getting shortlisted
- Practice real-world NLP concepts
- Python
- Streamlit
- Scikit-learn (TF-IDF, Cosine Similarity)
- NLTK (Text Processing)
- PyPDF2 (PDF Extraction)
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Upload your resume
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Upload or paste a job description
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The app:
- Cleans and processes text
- Converts text into numerical vectors (TF-IDF)
- Calculates similarity using cosine similarity
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Outputs:
- Match Score (%)
- Missing Keywords
- Matching Keywords
👉 https://resume-analyzer-jpxdam6zashi8ghporuvvk.streamlit.app/
pip install -r requirements.txt
streamlit run app.py- Practical use of NLP in real-world problems
- How ATS systems work
- Building and deploying web apps using Streamlit
- Working with GitHub and deployment tools
- 🤖 AI-based resume suggestions (LLM integration)
- 📊 Better visual analytics
- 🎯 Role-specific keyword recommendations
I am a fresher passionate about Data Analytics and building real-world projects.
This project is something I actively use during my job search to improve my resume.
🔗 GitHub: https://github.com/Bella1801
If you find this project useful, feel free to give it a ⭐!