🔍 Resume Screening System — Future Interns ML Task 3 (2026)

An ML-powered resume screening and candidate ranking system built with NLP techniques.

📌 Overview

This system automatically screens, scores, and ranks resumes against a given job description using:

• Text Preprocessing — cleaning, tokenization, lemmatization
• Skill Extraction — NLP-based keyword matching against a skill taxonomy
• TF-IDF Vectorization + Cosine Similarity — semantic resume-to-JD matching
• Candidate Ranking — composite scoring with skill gap analysis
• Interactive Dashboard — Streamlit UI for recruiters

🗂️ Project Structure

FUTURE_ML_03/
├── data/
│   └── resume_dataset.csv        # Kaggle dataset (snehaanbhawal)
├── notebooks/
│   └── resume_screening.ipynb    # Full EDA + model notebook
├── app/
│   └── streamlit_app.py          # Recruiter-facing dashboard
├── src/
│   ├── preprocessor.py           # Text cleaning pipeline
│   ├── skill_extractor.py        # NLP skill extraction
│   ├── scorer.py                 # Similarity scoring & ranking
│   └── skill_taxonomy.py         # Curated skill keyword list
├── requirements.txt
└── README.md

🚀 Setup & Run

# 1. Clone the repo
git clone https://github.com/Lami14/FUTURE_ML_03.git
cd FUTURE_ML_03

# 2. Install dependencies
pip install -r requirements.txt

# 3. Download spaCy model
python -m spacy download en_core_web_sm

# 4. Add dataset
# Download from: https://www.kaggle.com/datasets/snehaanbhawal/resume-dataset
# Place resume_dataset.csv in the data/ folder

# 5. Run the dashboard
streamlit run app/streamlit_app.py

📊 How Scoring Works

Each resume receives a composite score (0–100) based on:

Component	Weight	Description
Skill Match	50%	% of required skills found in resume
TF-IDF Similarity	35%	Cosine similarity to job description
Experience Bonus	15%	Years/seniority signals in text

Candidates are then ranked highest → lowest with a full skill gap report.

🛠️ Tech Stack

• Python 3.10+
• spaCy en_core_web_sm
• NLTK
• scikit-learn
• pandas / numpy
• Streamlit
• matplotlib / plotly

📁 Dataset

Resume Dataset by Sneha Anbhawal (Kaggle)
🔗 https://www.kaggle.com/datasets/snehaanbhawal/resume-dataset

Contains 2,484 resumes across 25 job categories in CSV format.

👤 Author

Lamla Mhlana
Future Interns — ML Internship Track, Task 3 (2026)
GitHub: @Lami14