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.
(or)
To buy this project in ONLINE, Contact:

📌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