AI-Resume-Parser-and-Resume-Analyzer

AI-powered Resume Parser and Analyzer built using NLP, Machine Learning, and Streamlit. Upload PDF resumes to get resume category prediction, skill extraction, resume scoring, and AI-based recommendations using TF-IDF and SVM models.

This application allows users to upload PDF resumes and get intelligent resume analysis including:

Resume Category Prediction, Skill Extraction, Resume Scoring, AI-Based Recommendations

The project uses TF-IDF vectorization and SVM classification for resume categorization.

Features

✅ Upload PDF Resume

✅ Extract Resume Text

✅ Resume Category Prediction

✅ Skill Extraction

✅ Resume Score Generation

✅ AI Recommendations

✅ NLP-Based Resume Processing

✅ Machine Learning Classification

✅ Interactive Streamlit Web App

Tech Stack

Python, Streamlit, NLTK, scikit-learn, pdfplumber, TF-IDF Vectorization, SVM (Support Vector Machine).

Project Structure

AI-Resume-Parser/ │

├── dataset/

│ └── Resume.csv

│

├── app.py

├── save_model.py

├── model.pkl

├── tfidf.pkl

├── requirements.txt

│

└── venv/

How It Works

User uploads a PDF resume

PDF text is extracted using pdfplumber

Resume text is cleaned using NLP preprocessing

TF-IDF converts text into vectors

SVM model predicts resume category

Skills are extracted from resume

Resume score is calculated

AI recommendations are displayed

Future Enhancements

ATS Compatibility Checker, Job Recommendation System, Resume Ranking, Multi-language Resume Support, AI Chat Assistant, Resume Improvement Suggestions, Cloud Deployment

Dataset

Kaggle Resume Dataset

Author

Himabindu Karri

Support

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License

This project is developed for educational and portfolio purposes.