This project is about the prediction of red wine quality using different machine learning algorithms

🍾 A comprehensive machine learning project using Random Forest algorithm to predict wine quality based on physicochemical properties. Features EDA, model training, hyperparameter tuning, feature importance analysis, and detailed documentation.

Wine Quality Prediction using machine learning with python .i did this project in AINN(Artificial Intelligence and Neural Network) course .in this project i used red and white wine databases and machine learning libraries available in python

This project performs **exploratory data analysis (EDA)** and **multidimensional visualizations** on the UCI Wine Quality dataset (Red & White wines).

Used Multiple Linear Regression which will predict the quality of wine using 11 features.

Building classification models to predict quality of wines. (Accuracy = 71.33%)

Train a neural network to predict the quality of red-wine using chemical properties such as pH, density, alcohol percentage etc.

Wine Predicts

Wine Quality Prediction Model (ML) ExtraTreesClassifier 88% Accuracy

Uses logistic regression to predict the quality of wine based on various physicochemical properties.

This project explores the red‑wine quality dataset and trains a Random Forest classifier to predict the quality of the wine based on its features.

Previsão de Qualidade de Vinho com Redes Neurais Este repositório contém uma aplicação Flask que utiliza uma rede neural para prever a qualidade do vinho com base em suas características.

ML algorithms for Regression, Classification, Clustering and Dimensional Reduction applied in a Wine Quality Dataset.

K means clustering implementation on the wine quality dataset

This repository implements a full end-to-end Data Science project using the wine quality dataset

Implementation of various ML algorithms and their application to real world problems

Empowering Advanced Text Classification and Wine Quality Prediction with Cutting-Edge Machine Learning Techniques.

ANN model which predicts wine quality

A web app featuring five classification projects: Spam Mail Prediction, Titanic Survival Prediction, Wine Quality Prediction, Loan Status Prediction, and Credit Card Fraud Detection, all built with Streamlit.