AI Resume Screener — DistilBERT fine-tuned on 43 job categories, 88% accuracy, deployed on HuggingFace Spaces
This project simulates an AI-powered resume screening system that extracts and analyzes candidate information such as skills, experience, and tools.
An AI-powered tool that helps recruiters automatically screen resumes against a given job description. This project reduces HR workload by analyzing resumes (manual uploads or Gmail attachments) and scoring them based on semantic similarity.
An applied AI pipeline that classifies uploaded documents, extracts candidate data, verifies claims, and ranks resumes against job descriptions.
An agentic LangGraph pipeline that evaluates candidate-job fit using structured LLM reasoning to generate evidence-backed hiring recommendations.
AI-powered Resume Screener using Scikit-learn, featuring text preprocessing, TF-IDF vectorization, and ML models (Logistic Regression, SVM, Random Forest) to classify and rank resumes for automated recruitment.
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