An AI-powered Resume Classification System that automatically categorizes resumes into different job roles using Natural Language Processing (NLP) and Machine Learning. This project helps recruiters automatically screen resumes and classify candidates based on their skillset and experience.
• Automatic resume category prediction
• NLP-based text preprocessing
• TF-IDF feature extraction
• Machine Learning classification model
• Supports multiple resume formats (DOC, DOCX, PDF)
• Fast prediction using saved ML models
Python
Scikit-learn
Pandas
NumPy
NLTK
TF-IDF Vectorization
Decision Tree Classifier
Flask (for web application)
The dataset contains resumes from multiple domains including:
- React Developer
- SQL Developer
- Peoplesoft
- Workday
Each resume is labeled according to its respective job category.
- Resume text extraction
- Text preprocessing
- Lowercasing
- Removing special characters
- Stopword removal
- Feature Extraction using TF-IDF Vectorizer
- Model training using Decision Tree Classifier
- Model serialization using Pickle
- Resume category prediction
Resume Input
↓
Text Preprocessing
↓
TF-IDF Vectorization
↓
Machine Learning Model
↓
Predicted Job Role
Clone the repository
git clone https://github.com/yourusername/resume-classifier-ml.gitInstall dependencies
pip install -r requirements.txtRun the application
python app.pyInput Resume →
Skills: React, JavaScript, HTML, CSS
Predicted Category →
React Developer
• Deep Learning based classification (BERT / Transformers)
• Resume ranking system
• Skill extraction module
• Recruiter dashboard
• Integration with job portals
Randeep Raj
AI / ML Engineer | Data Science Enthusiast
This project is licensed under the MIT License.