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Task Submission - DAS001776 - Project Topic Recommender

Task Submission: Project Topic Recommender

Student: Priyanshi Trehan (DAS001776)

Domain: AI & Data Science

Internship ID: 182

Task Submission – DAS001776 – Project Topic Recommender

As part of my AI & Data Science Internship, I recently completed Task DAS001776 – Project Topic Recommender. This project was focused on building an intelligent recommendation system that helps users discover AI project ideas based on their interests, skills, preferred domain, and difficulty level.

While working on this project, I explored how recommendation systems can be used to solve a common problem faced by many students—finding the right project to work on. Instead of manually searching through hundreds of project ideas, users can simply provide their preferences and receive personalized recommendations within seconds.

To build this system, I used Natural Language Processing (NLP) for text preprocessing, TF-IDF Vectorization for converting text into numerical features, and Cosine Similarity to identify the most relevant project ideas. Along with the recommendations, the system also provides a Match Score, explains why a project was recommended, highlights the skills the user should learn, and suggests useful learning resources.

✨ Features of the Project

  • Personalized AI project recommendations
  • NLP-based text preprocessing
  • TF-IDF Vectorization
  • Cosine Similarity for recommendation matching
  • Match Score for every recommendation
  • Explainable recommendations
  • Skill Gap Analysis
  • Learning resource suggestions
  • Export recommendations to CSV

🛠️ Technologies Used

  • Python
  • Pandas
  • NumPy
  • NLTK
  • Scikit-learn
  • TF-IDF Vectorizer
  • Cosine Similarity

📚 What I Learned

This project gave me practical exposure to building a recommendation system using NLP techniques. I improved my understanding of text preprocessing, feature extraction, similarity calculations, and organizing a complete Python project from development to documentation. It also helped me strengthen my problem-solving skills and gain confidence in implementing AI concepts in a real-world application.

🔗 GitHub Repository

Project Link:

https://github.com/priyanshi2312/AI-Project-Topic-Recommender

Overall, this was a valuable learning experience that allowed me to apply AI and Machine Learning concepts in a practical project. I look forward to building more innovative projects and continuing my learning journey in the field of Artificial Intelligence and Data Science.

Thank you for reading!

Project Resources

Video Demonstration
Task Demo - DAS001776 - Project Topic Recommender | AI Project Recommendation System
This video demonstrates the AI Project Topic Recommender developed as part of Task DAS001776.

The system recommends personalized AI project ideas based on the user's interests, skills, preferred domain, and difficulty level. It uses Natural Language Processing (NLP), TF-IDF Vectorization, and Cosine Similarity to generate accurate project recommendations along with match scores, skill gap analysis, and learning resources.

✨ Features:
• Personalized AI project recommendations
• NLP-based text preprocessing
• TF-IDF Vectorization
• Cosine Similarity matching
• Match Score for each recommendation
• Explainable recommendations
• Skill Gap Analysis
• Learning Resource Suggestions
• Export recommendations to CSV

🛠️ Technologies Used:
• Python
• Pandas
• NumPy
• NLTK
• Scikit-learn
• TF-IDF Vectorizer
• Cosine Similarity

🔗 GitHub Repository:
https://github.com/priyanshi2312/AI-Project-Topic-Recommender

If you found this project helpful, don't forget to Like, Share, and Subscribe!

#ArtificialIntelligence #MachineLearning #Python #NLP #TFIDF #CosineSimilarity #AIProjects #RecommendationSystem #DataScience #GitHub
Watch on YouTube
GitHub Repository
priyanshi2312/AI-Project-Topic-Recommender
View on GitHub
P
Priyanshi Trehan DAS001776 Student

Student at Free Internships - Sharing my internship journey and experiences.

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