AI Recommendation System 🎯

Project 3 | DecodeLabs Industrial Training | Batch 2026 Developer: Mayar Yasser

Overview

A content-based recommendation system that maps a user's skills to the most relevant tech job roles using TF-IDF vectorization and Cosine Similarity.

How It Works

• User enters 3 skills
• System converts skills to TF-IDF vectors
• Cosine Similarity calculated against all job roles
• Top 3 most relevant careers returned

Two Approaches Used

Approach 1: Simple Matching (Basic)

Counts overlapping skills between user and job roles.

Approach 2: TF-IDF + Cosine Similarity (Upgraded) ✅

Converts skills to weighted vectors and measures angular similarity for more accurate matching.

Example

Input: python, machine_learning, sql Output:

Data Scientist — 52% match ML Engineer — 38% match Backend Developer — 29% match

How to Run

python recommender.py

Tools Used

• Python
• pandas
• scikit-learn (TF-IDF + Cosine Similarity)

Screenshot

Developer

Mayar Yasser | DecodeLabs Batch 2026