Popular GitHub Repositories for Candidates

Developed an AI application using LLM to analyze user resumes and provided the summarization, strengths, weaknesses, suggestions, suitable job titles, and also scraping job details from LinkedIn using Selenium. This application reduces time by 30% and helps candidates tailor their resumes effectively.

Thematic Generalization Benchmark: measures how effectively various LLMs can infer a narrow or specific "theme" (category/rule) from a small set of examples and anti-examples, then detect which item truly fits that theme among a collection of misleading candidates.

Revolutionize your recruitment process with this cutting-edge proof of concept! Developed from the inspiration of josephkearney91's LinkedIn scraping project, this advanced tool harnesses the capabilities of the OpenAI API (Chat GPT) to craft and send customized messages to prospective candidates across various languages.

Structural Constraint Integration in Generative Model for Discovery of Quantum Material Candidates

Automating the vetting and validation of planet candidates from photometry survey missions - Kepler and TESS - using deep learning methods

A simple Django-based resume ranker website where recruiters post their jobs and candidates applies for their desired vacancies. The system gets the document similarity between the job description and the candidate resumes, generates similarity scores using the KNN model, and rank or shortlist the candidate resumes.

In this mini-project i have chosen to do sentiment analysis of social media websites such as twitter and reddit to gain insights into the people’s opinion towards prime ministerial candidates for the Lok Sabha election 2019. Social media provides a platform for people’s opinion of a person or event or topic to be heard from anywhere at any time and is the easiest and fastest way for them to do it. So, analysing these sentiments will be of immense use in knowing the trending topics and the mood of the people towards those topics among other things. The mini-project also aims at implementing and comparing contemporary machine learning text classification algorithms to predict the sentiment of a piece of text.

RucRut is an AI-powered recruitment system that streamlines the hiring process by automatically generating interview questions, evaluating candidate responses, and providing real-time feedback. It leverages Natural Language Processing (NLP) to enhance recruitment efficiency for job providers and candidates.

Resume Analyzer is a C++ tool that reads resumes, matches them with required skills, ranks them using heaps based on experience and skill relevance, and displays top candidates—all through a menu-driven console interface.

An NLP based Web-App that asks the user to input some Job Posting along with a candidate to list to give scores to the candidates based on their proficiency in the job profile required as an output.

Build an AI-powered Hiring Agent using Google ADK and Gemini 3 to analyze resumes, assess skills, and match candidates to roles through intelligent, multi-agent collaboration.

Using deep learning to generate novel molecules as candidates for binding with coronavirus protease

InterviewMate is an innovative AI-powered interview assistant designed to streamline the interview process for both candidates and interviewers. With its intelligent features, InterviewMate aims to assist users in preparing for, conducting, and analyzing interviews effectively.

The AI-Based Pre-Screening Assistant Bot is an AI-powered technical interview assistant that evaluates candidates using adaptive questioning, real-time feedback, and automated report generation. Built with Streamlit and RAGPipeline, it dynamically adjusts question complexity, tracks candidate performance, and emails interview summaries

CV Embed is an AI resume analyzer that matches candidates with job descriptions using SBERT/GloVe/Doc2Vec models. Calculates compatibility scores, suggests top job matches, and generates real opportunities. Supports PDF/DOCX uploads with Flask backend and Gemini AI integration.

This project uses Natural Language Processing (NLP) to automate resume parsing and rank candidates based on job relevance. It enables recruiters to efficiently shortlist the best candidates by extracting structured information from resumes and matching them against job descriptions.

Smart ATS Sytem that can search for the best candidates according to the job description similarity from a vector database of resume documents using RAG and recommend the best candidate using LLM

SATS (Smart Applicant Tracking System) is an advanced recruitment tool that uses contextual understanding and comprehensive analysis to evaluate candidates based on education, experience, and expertise. It includes features like contextual analysis and a leaderboard system, making recruitment more efficient and accurate.

Guruji is an AI-powered interview platform that automates the creation, scheduling, and execution of technical interviews. Leveraging modern web technologies and AI/voice services, Guruji offers a seamless experience for recruiters and candidates alike.

The goal of this application is to generate suggestions based on the given resume of the candidate, store the candidate profile in Pinecone database, and shortlist candidates accroding to the skills matched with match score.