{"id":19139715,"url":"https://github.com/kunalshelke90/wine-quality-testing","last_synced_at":"2026-04-10T07:03:02.435Z","repository":{"id":251105118,"uuid":"836391951","full_name":"kunalshelke90/Wine-Quality-Testing","owner":"kunalshelke90","description":"This project is about creating a machine learning algorithm that can predict the quality of wine based on the given dataset. 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The classes are ordered and not balanced (e.g. there are much more normal wines than excellent or poor ones).Your task is to predict the quality of wine using the given data.\n\n\n# Dataset Link\n\nhttps://archive.ics.uci.edu/dataset/186/wine+quality\n\n\n## Run Locally\n\nClone the project\n\n```bash\n    git clone https://github.com/kunalshelke90/Wine-Quality-Testing.git\n```\n\nGo to the project directory\n\n```bash\n    cd Wine-Quality-Testing\n```\n\nCreate a virtual environment and install dependencies:\n\n```bash\n    conda create -p myenv python=3.8 -y\n```\n\n\n```bash\n   conda activate myenv\n```\n```bash\n    pip install -r requirements.txt\n```\n\n## Usage\n1. Start the Flask application:\n\n```bash\n    python app.py\n```\n2. Access the application:\nOpen your web browser and go to http://localhost:8080 to interact with the application. or http://127.0.0.1:8080\n\n# Steps included in this project:\n\n    Importing Lib\n    Loading Data\n    Understanding Data\n    Missing Values\n    Exploring Variables(Data Anylasis)\n    Feature Selection\n    Proportion of Good vs Bad Wines\n    Preparing Data for Modelling\n    Applying different models\n    Choosing right model\n    Start doing prediciton\n    \n# ## Workflows\n\n1. update config.yaml\n   \n2. update schema.yaml\n   \n3. update params.yaml\n \n4. update the entity\n\n5. update the configuration manager in src config\n  \n6. update the components\n  \n7. update the pipeline\n   \n8. update the main.py\n\n9. update the app.py\n\n# Learning\n\nI learned how machine learning explainability can be used to take a deep dive into machine learning models and extract key insights that can be used in the real world. I also learned that the highest quality of wine had an alchoal content between 12% - 15%.\n\n# License\n\nThis project is licensed under the MIT License. See the LICENSE file for details\n\nCHEERS!\n\n\u003cimg src=\"http://media-cdn.tripadvisor.com/media/photo-s/10/28/86/6f/wine-cheers.jpg\"\u003e\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkunalshelke90%2Fwine-quality-testing","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fkunalshelke90%2Fwine-quality-testing","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkunalshelke90%2Fwine-quality-testing/lists"}