This innovative career recommendation system is designed specifically for students in India. It leverages a dataset of top Indian LinkedIn profiles working in India to provide personalized guidance, helping students understand and excel in the complex Indian job market. It uses advanced data processing techniques and machine learning for precise career path prediction.
-Personalized Career Mapping: Detailed exploration of careers, emphasizing the differences and interrelations between job roles.
-Advanced Data Processing: Utilizes Selenium for web scraping, along with ChatGPT API and NLTK for text processing.
-Machine Learning Model: Combination of TF-IDF, TruncatedSVD, and XGBClassifier for accurate career predictions.
-Innovative Clustering Technique: Custom mechanism to match student profiles with a diverse range of job roles.
-High Accuracy: 95% success rate in career path predictions.
-Balanced Metrics: Approximately 90% in precision, recall, and F1-scores.
-Multi-dimensional Career Insights: Provides diverse insights into potential career paths.
A student considering a Data Scientist role might discover alignment with other roles like Machine Learning Engineer or Quant Engineer, broadening their career options.
FinalProjectRepo/codes/
-XGBoost Classification Code.ipynb - Code for the XGBoost classifier.
-data_augmentation.ipynb - Notebook for data augmentation techniques.
-keyword_extracter.ipynb - Script for extracting keywords from profiles.
-linkedin_scraper.ipynb - Selenium-based LinkedIn scraper.
-model - clustering.ipynb - Notebook for the custom clustering model.
-parsed_resume.txt - Sample parsed resume.
-resume.py - Python script for resume parsing.
-skills_about.ipynb - Notebook for skills and about section processing.
Final Project Presentation.pdf can be found at FinalProjectRepo/FinalPresentationReport.pdf
or on the course project link of Plaksha University:
Project name: Job Recommendation System for Plaksha Students
https://ai3011.plaksha.edu.in/monsoon2023.html
Applied Machine Learning
Data Scraping & Pre-processing
Natural Language Processing (NLP)
Statistical Analysis & Feature Engineering
Predictive Modeling