A Machine Learning Based Approach for Wine Quality Prediction | Python Final Year IEEE Project

A Machine Learning Based Approach for Wine Quality Prediction | Python Final Year IEEE Project. 🛒Buy Link: https://bit.ly/40PonnE (or) To buy this project in ONLINE, Contact: 🔗Email: [email protected], 🌐Website: https://www.jpinfotech.org 📌Project Title: A Machine Learning Based Approach for Wine Quality Prediction. 💡Implementation Code: Python. 🚀Algorithm / Model Used: Random Forest Classifier. 🌐Web Framework: Flask. 🖥️Frontend: HTML, CSS, JavaScript. 💰Cost (In Indian Rupees): Rs.3000/. 📘Project Abstract: 👉Machine learning models are crucial tools today for replacing human labour. There are a number of features that can be used to forecast the wine quality in this scenario, but not all of the attributes will be useful for a more accurate prediction. We utilised the Random Forest Classifier technique to create a classification model. We used the Vinho Verde dataset from Kaggle for this project. 👉The proposed method in this research uses a Random Forest Classifier to identify the wine based on its components, which helps us predict the quality of wine. We also designed a user interface using the Flask web framework to make the task much more user-friendly. 📌REFERENCE: Basvaraj. S. Anami, Kavita Mainalli, Shanta Kallur, Vijeeta Patil, “A Machine Learning Based Approach for Wine Quality Prediction”, 2022 2nd Asian Conference on Innovation in Technology (ASIANCON), IEEE Conference, 2022. 🏷️tags: #python #pythonprojects #wine #quality #predictions #machinelearningproject #pythonprogramming #pythonprojectforbeginners #pythonprojectideas #pythonmachinelearning #machinelearning #machinelearningpython #finalyearproject #ieeeprojects #finalyearprojects #datascience #datascienceproject #artificialintelligenceproject #projects #deeplearning #deeplearningproject #computerscienceproject #deeplearningprojects #majorprojects #academicprojects #majorprojects