This is base-line approach for building job recommendation engine
-
Updated
Apr 11, 2018 - Python
This is base-line approach for building job recommendation engine
This repository contains code how to build job recommendation engine using Kaggle 'Job Recommendation Challenge' dataset
Our solution for Recsys Challenge 2017.
Aim is to come up with a job recommender system, which takes the skills from LinkedIn and jobs from Indeed and throws the best jobs available for you according to your skills.
Job recommendation system using NLP, in which a user’s description is evaluated via a trained NLP model and jobs are suggested based on the similarities between the user’s skill set and the job’s required skill set. Jobs are scraped from various trustworthy sites in real time using Selenium and stored in a database.
DS307.N11 - Phân Tích Dữ Liệu Truyền Thông Xã Hội
Our extensions to KRED: Knowledge-Aware Document Representation for News Recommendations
One stop for Guided path, learning resources, projects, research and development and latest trends
Several baseline models and PJFNN on Job Recommendation Challenge
A simple job recommendation system project (using Python) for my final year!
Revolutionizing Job Search with Personalized AI-Powered Recommendations
CollegeSpace brings together the brightest minds and operators across the world to solve complex problems and build the future.
This job recommendation system helps connect candidates with suitable opportunities by analyzing skills. It combines data from Stack Overflow's 2018 Developer Survey and a Kaggle dataset.Improved job-candidate matching for a more efficient hiring process. Personalized recommendations based on skills and past successes.
Add a description, image, and links to the job-recommendation topic page so that developers can more easily learn about it.
To associate your repository with the job-recommendation topic, visit your repo's landing page and select "manage topics."