An AI-driven resume classification tool leveraging NLP, TF-IDF, and Machine Learning to automatically categorize resumes into job roles with high accuracy.

SKILLSCAN AI is a cutting-edge resume categorization system that processes resumes and classifies them into multiple job roles using TF-IDF vectorization and multiple ML models:

• Java Developer
• Python Developer
• Data Scientist
• DevOps Engineer
• Machine Learning Engineer
• And many more...

By utilizing TF-IDF + Logistic Regression, Random Forest, KNN, and Naive Bayes, SKILLSCAN AI achieves high classification accuracy while maintaining a fast and scalable pipeline.

✅ Fast & Accurate: ML models trained for resume categorization with up to 99% accuracy.
✅ TF-IDF Feature Extraction: Advanced text processing for better classification.
✅ Multi-Model Comparison: Uses Logistic Regression, SVC, KNN, Naive Bayes, and Random Forest.
✅ Explainability with Confusion Matrix & Radar Charts: Visual insights into model performance.

📌 Dataset: Custom dataset of 20+ job categories.
📌 Data Preprocessing: Includes text cleaning, stopword removal, and TF-IDF transformation.

Overall Metrics

• Feature Extraction: TF-IDF Vectorization.
• Models Used: Logistic Regression, Random Forest, KNN, Naive Bayes, and SVC.
• Loss Function: Categorical Crossentropy (for multi-class classification).
• Optimizer: GridSearchCV to fine-tune hyperparameters.
• Evaluation Metrics: Accuracy, F1-Score, Precision, Recall, and Confusion Matrix.

• Python
• Scikit-Learn
• NLTK
• TF-IDF Vectorizer
• Seaborn / Matplotlib (for visualization)
• Jupyter Notebook

📧 Email: utkarshranaa06@gmail.com
🔗 GitHub: utkarshranaa
🔗 LinkedIn: www.linkedin.com/in/utkarshranaa
🔗 X/Twitter: @utkarshranaa

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