Online Job Portal Application using Machine Learning

In the rapidly evolving job market, an efficient and personalized job portal plays a pivotal role in connecting job seekers with suitable opportunities. This project aims to develop a comprehensive job portal application by integrating various machine learning algorithms, enhancing user experience and job matching accuracy. The key components include Natural Language Processing (NLP), K-Nearest Neighbors (KNN), skill matching, job recommendation, resume parsing, and Decision Tree-based decision-making. This project aims to create a dynamic and intelligent job portal that not only streamlines the job search process but also provides a personalized and efficient experience for both job seekers and employers. The amalgamation of NLP, K-Nearest Neighbors, skill matching, recommendation systems, resume parsing, and decision trees forms a robust framework for enhancing the functionality and activeness of the job portal application.