{"id":31164239,"url":"https://github.com/gehad-ahmed30/recommender_system","last_synced_at":"2026-06-19T06:32:22.172Z","repository":{"id":303879255,"uuid":"1017006284","full_name":"gehad-Ahmed30/Recommender_system","owner":"gehad-Ahmed30","description":"A content-based recommender system for Udemy courses using NLP and cosine similarity.   It analyzes course titles to suggest similar courses based on keyword relevance.   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The system suggests similar courses based on course titles using **Natural Language Processing (NLP)** and **Cosine Similarity**.\n\n---\n\n## 📁 Dataset\nThe dataset used contains metadata about Udemy courses such as:\n- Course title\n- Price\n- Number of subscribers\n- Level\n- Subject\n- Published date\n- Profit\n\n---\n\n## 🛠️ Technologies \u0026 Libraries Used\n\n- Python\n- pandas, numpy\n- matplotlib, seaborn\n- `neattext` for text preprocessing\n- `sklearn` for feature extraction and similarity calculation\n\n---\n\n## 🔎 Steps in the Project\n\n1. **Data Import \u0026 Exploration**\n   - Load and explore the Udemy dataset\n2. **Data Preprocessing**\n   - Clean course titles by removing stopwords and special characters\n3. **Feature Extraction**\n   - Use `CountVectorizer` to convert course titles into token vectors\n4. **Similarity Calculation**\n   - Compute **Cosine Similarity** between all course titles\n5. **Recommendation Engine**\n   - Build a function to recommend similar courses based on a selected title\n\n---\n\n## 📦 How to Use\n\nYou can call the main function:\n\n```python\nrecommend_course('Beginner to Pro - Financial Analysis in Excel 2017', numrec=5)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgehad-ahmed30%2Frecommender_system","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fgehad-ahmed30%2Frecommender_system","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgehad-ahmed30%2Frecommender_system/lists"}