{"id":28923940,"url":"https://github.com/prajjwal6969/recommender-system-using-python","last_synced_at":"2026-05-08T14:32:15.465Z","repository":{"id":299878148,"uuid":"1004512820","full_name":"Prajjwal6969/Recommender-System-using-Python","owner":"Prajjwal6969","description":"A collection of content-based recommendation systems for songs and movies using Python and machine learning.","archived":false,"fork":false,"pushed_at":"2025-06-18T18:50:27.000Z","size":9650,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-06-18T19:42:51.673Z","etag":null,"topics":["content-based-filtering","cosine-similarity","machine-learning","movie-recommendation","python","recommender-system","scikit-learn","song-recommendation"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Prajjwal6969.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2025-06-18T18:36:03.000Z","updated_at":"2025-06-18T19:07:07.000Z","dependencies_parsed_at":"2025-06-18T19:42:55.672Z","dependency_job_id":"838f060c-5a73-4b12-891b-978c14b127e7","html_url":"https://github.com/Prajjwal6969/Recommender-System-using-Python","commit_stats":null,"previous_names":["prajjwal6969/recommender-system-using-python"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/Prajjwal6969/Recommender-System-using-Python","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Prajjwal6969%2FRecommender-System-using-Python","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Prajjwal6969%2FRecommender-System-using-Python/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Prajjwal6969%2FRecommender-System-using-Python/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Prajjwal6969%2FRecommender-System-using-Python/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Prajjwal6969","download_url":"https://codeload.github.com/Prajjwal6969/Recommender-System-using-Python/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Prajjwal6969%2FRecommender-System-using-Python/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":264766583,"owners_count":23660801,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["content-based-filtering","cosine-similarity","machine-learning","movie-recommendation","python","recommender-system","scikit-learn","song-recommendation"],"created_at":"2025-06-22T10:02:22.089Z","updated_at":"2026-05-08T14:32:15.414Z","avatar_url":"https://github.com/Prajjwal6969.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# 🎯 Recommender Systems Collection\n\nThis repository contains two mini-projects built using Python and machine learning for content-based recommendation:\n\n- 🎵 **Song Recommender System**\n- 🎬 **Movie Recommender System**\n\nBoth projects demonstrate how similarity metrics and feature engineering can be used to recommend relevant items to users.\n\n---\n\n## 🔍 Project 1: Song Recommender System\n\n### 📌 Description:\nThis project recommends songs based on audio features using **content-based filtering**. It analyzes attributes like danceability, energy, tempo, valence, etc., and uses similarity metrics to suggest songs that sound similar.\n\n### 🧠 Methodology:\n- Features Used:\n  - Danceability\n  - Energy\n  - Valence\n  - Tempo\n  - Acousticness\n  - Liveness\n- Techniques:\n  - Cosine Similarity or K-Nearest Neighbors\n  - Feature scaling and preprocessing\n\n### ✅ Output:\nGiven a song name, it returns a list of similar songs based on their audio characteristics.\n\n---\n\n## 🎥 Project 2: Movie Recommender System\n\n### 📌 Description:\nThis system recommends movies based on genres, cast, director, and keywords using **content-based filtering**. The project builds a \"tag\" feature by combining various metadata.\n\n### 🧠 Techniques Used:\n- Text preprocessing and vectorization using `CountVectorizer` or `TfidfVectorizer`\n- Cosine Similarity to calculate similarity between movies\n- Metadata parsing (cast, crew, overview, genres)\n\n### 🛠️ Input:\n- User provides a movie name.\n\n### 🎯 Output:\n- Returns top 5–10 similar movies.\n\n---\n\n## 📁 How to Use\n\n1. Clone the repository:\n   ```bash\n   git clone https://github.com/Prajjwal6969/recommender-systems.git\n   cd recommender-systems\n2. Install required libraries:\n    pip install -r requirements.txt\n   \n4. Launch the Jupyter notebooks:\n    jupyter notebook\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fprajjwal6969%2Frecommender-system-using-python","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fprajjwal6969%2Frecommender-system-using-python","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fprajjwal6969%2Frecommender-system-using-python/lists"}