Task Submission - DAS003048 - Recommendation Engine

Task Submission: Recommendation Engine

Student: Niharika Talabhuttula (DAS003048)

Domain: AI & Data Science

Internship ID: 791

Project Overview

Task Title: Recommendation Engine

Description: Create a recommendation engine for internship suggestions, project recommendations, and learning resources.

Domain Summary

The AI Internship Recommendation Engine is a machine learning-based recommendation system designed to help students discover internships that best match their skills, academic background, interests, career goals, and preferred locations. Finding the right internship from hundreds of available opportunities can be challenging, and this project addresses that problem by providing personalized recommendations.

The system uses a Hybrid Recommendation Approach, combining Content-Based Filtering and Collaborative Filtering techniques. Content-Based Filtering recommends internships by comparing a student's profile with internship requirements, while Collaborative Filtering analyzes the preferences and ratings of similar students. By integrating both methods, the system generates more accurate and relevant internship recommendations.

This project demonstrates how Artificial Intelligence and Machine Learning can be applied to solve real-world career guidance problems and assist students in making informed internship decisions.

Technologies Used

The project was developed using the following technologies and libraries:

Python – Core programming language used to implement the recommendation system.

Pandas – Used for data loading, preprocessing, manipulation, and analysis.

NumPy – Used for numerical computations and efficient data handling.

Scikit-learn – Used for implementing similarity calculations and recommendation algorithms.

Streamlit – Used to build an interactive web-based dashboard for users to access recommendations.

Plotly – Used to create interactive charts and visualizations for recommendation analysis.

CSV Files – Used to store student profiles, internship details, and rating data for the prototype implementation.

Git & GitHub – Used for version control, project management, and source code hosting.

These technologies work together to create a scalable and user-friendly recommendation engine that provides personalized internship suggestions efficiently.

How I Completed This Task

I completed this task by following the project requirements and implementing the necessary features.

Outcome

The task was completed successfully with all requirements met.