{"id":25238659,"url":"https://github.com/daksh90a/wine-quality-analysis","last_synced_at":"2026-05-12T07:41:49.658Z","repository":{"id":276786323,"uuid":"930298310","full_name":"Daksh90a/Wine-Quality-Analysis","owner":"Daksh90a","description":"The Wine Quality Analysis project is an AI/ML-based data analysis initiative aimed at predicting and understanding the factors that influence the quality of wine.","archived":false,"fork":false,"pushed_at":"2025-02-10T12:14:34.000Z","size":188,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-05T19:36:07.958Z","etag":null,"topics":["matplotlib-python","numpy","pandas","seaborn"],"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/Daksh90a.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}},"created_at":"2025-02-10T12:09:43.000Z","updated_at":"2025-02-10T12:16:05.000Z","dependencies_parsed_at":"2025-02-10T12:40:34.400Z","dependency_job_id":"637f3cd6-53b6-43ea-877c-99ee78089514","html_url":"https://github.com/Daksh90a/Wine-Quality-Analysis","commit_stats":null,"previous_names":["daksh90a/wine-quality-analysis"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Daksh90a%2FWine-Quality-Analysis","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Daksh90a%2FWine-Quality-Analysis/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Daksh90a%2FWine-Quality-Analysis/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Daksh90a%2FWine-Quality-Analysis/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Daksh90a","download_url":"https://codeload.github.com/Daksh90a/Wine-Quality-Analysis/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247393558,"owners_count":20931809,"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":["matplotlib-python","numpy","pandas","seaborn"],"created_at":"2025-02-11T17:53:06.013Z","updated_at":"2026-05-12T07:41:49.617Z","avatar_url":"https://github.com/Daksh90a.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"Wine Quality Analysis - AI/ML Project\n\nProject Description:\n\nThe Wine Quality Analysis project is an AI/ML-based data analysis initiative aimed at predicting and understanding the factors that influence the quality of wine. Using Python and key data science libraries such as Pandas, NumPy, Seaborn, and Matplotlib, this project performs exploratory data analysis (EDA), visualization, and machine learning modeling to assess wine quality based on various physicochemical properties.\n\n------------------\n\nObjectives:\n\nAnalyze wine quality datasets to identify key factors affecting wine ratings.\n\nVisualize data trends and correlations using Seaborn and Matplotlib.\n\nPreprocess and clean data using Pandas and NumPy.\n\nBuild ML models (e.g., Logistic Regression, Random Forest, or Decision Trees) to predict wine quality.\n\nEvaluate model performance using metrics like accuracy, precision, and recall.\n\n-------------------------------------\n\nTechnologies \u0026 Libraries Used:\n\nPython (Primary programming language)\n\nPandas \u0026 NumPy (Data manipulation and preprocessing)\n\nSeaborn \u0026 Matplotlib (Data visualization and correlation analysis)\n\nScikit-learn (Machine learning model training and evaluation)\n\n--------------------------------------\n\nExpected Outcomes:\n\nA clear understanding of wine quality factors and their impact.\n\nAccurate ML models capable of predicting wine quality based on input features.\n\nInsightful data visualizations to interpret trends and relationships in the dataset.\n\nThis project is ideal for data enthusiasts and machine learning practitioners interested in data-driven decision-making in the food and beverage industry. 🍷📊\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdaksh90a%2Fwine-quality-analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdaksh90a%2Fwine-quality-analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdaksh90a%2Fwine-quality-analysis/lists"}