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AI & MLMini project
ML Resume Screening Tool
Parse resumes, extract skills with NLP, and score each candidate against a job description. A Streamlit app lets a recruiter upload files and see a ranked shortlist with the matching skills highlighted.
- Level
- Mini project
- Delivery
- 2–3 working days
- Stack
- Python, scikit-learn
- Best for
- Third-year and final-year B.Tech students
Features
- PDF and DOCX resume parsing
- Skill extraction with spaCy
- TF-IDF similarity scoring against a job description
- Ranked shortlist with matched skills
- Simple Streamlit interface
How it's built
The modules you'll walk through with our engineer.
- 01
Parsing
- Reading PDF and DOCX
- Text cleaning
- Section detection
- 02
Matching
- Skill extraction
- TF-IDF vectors
- Similarity scoring
- 03
Interface
- Streamlit upload flow
- Ranked results
- Export to CSV
Tech stack
Pythonscikit-learnspaCyStreamlit
What you get
- Complete source code with a README
- Sample dataset for testing
- Setup video for running it on your machine
- Project report template
- One 30-minute 1:1 walkthrough of the code
Best for
- Third-year and final-year B.Tech students
- BCA, MCA and M.Sc data science students
Learn it, don't just submit it
Every project comes with a 1:1 walkthrough
An engineer walks you through the architecture and code so you can extend it and answer viva questions with confidence. Check your institution's rules on using reference implementations before you submit.
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Get this project
Request ML Resume Screening Tool
- Delivered in 2–3 working days
- Customisations quoted before you pay
- Walkthrough booked at a time that suits you