ResumeScreen AI
Overview
This project leverages machine learning and natural language processing (NLP) to streamline the recruitment process by automating resume screening, categorization, and providing personalized job recommendations. The system extracts key information from resumes, categorizes them into predefined categories, and matches candidates with relevant job openings—optimizing the hiring workflow for recruiters and improving the experience for candidates.
Project Description
The traditional recruitment process can be tedious and prone to human bias. By integrating machine learning into recruitment, this project aims to revolutionize resume screening. The solution automates key tasks such as parsing resumes, categorizing them, and suggesting job recommendations based on extracted data.
Project Goals
Automate Resume Parsing : Extract key information like contact details, education, skills, and experience. Resume Categorization : Classify resumes into job categories using machine learning. Job Recommendations : Suggest suitable job openings for candidates based on their profiles.Key Features
1 . Resume Parsing :- Utilizes NLP techniques to extract and structure key information from resumes (e.g., contact information, skills, work experience). This eliminates manual data entry and ensures accurate results.
- Machine learning algorithms classify resumes into specific categories defined by recruiters. For instance, resumes could be grouped by job function such as Data Science, Software Development, or Marketing.
- The system uses machine learning to suggest relevant jobs to candidates based on their extracted skills and experiences, providing a personalized experience.