This repository contains code how to build job recommendation engine using Kaggle 'Job Recommendation Challenge' dataset
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Apr 11, 2018 - Jupyter Notebook
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This repository contains code how to build job recommendation engine using Kaggle 'Job Recommendation Challenge' dataset
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.
Our solution for Recsys Challenge 2017.
Several baseline models and PJFNN on Job Recommendation Challenge
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.
This is base-line approach for building job recommendation engine
A simple job recommendation system project (using Python) for my final year!
Our extensions to KRED: Knowledge-Aware Document Representation for News Recommendations
DS307.N11 - Phân Tích Dữ Liệu Truyền Thông Xã Hội
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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.
This projects serves as a web app to showcase the recommendation engine project
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AI Job Recommendation Platform Live Frontend: https://ai-job-recommend-front-end.vercel.app/ Live Backend: https://ai-job-recommend-backend.onrender.com/
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