Freelancer Job Analysis & Intelligent Recommendation System

Built an end-to-end system for analyzing freelance job markets and recommending relevant opportunities

using unsupervised clustering, Word2Vec embeddings, and supervised ML classification.

Implemented job clustering, skill-based recommendation, and job type classification (hourly vs fixed-price)

with TF-IDF, Logistic Regression, and cosine similarity.

Developed interactive visualizations and full-stack deployment using Streamlit, enabling real-time job

recommendations and market insights