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

This repository contains my machine learning models implementation code using streamlit in the Python programming language.

Linear discriminant Analysis(LDA) for Wine Dataset of Machine Learning

🍷 A project for analyzing red and white wine quality using R, combining exploratory visualizations, PCA, and a regression model to uncover chemical correlates of wine ratings. The script automates data fetching, cleaning, plotting, and modeling, offering a reproducible pipeline for statistical exploration.

Performed different tasks such as data preprocessing, cleaning, classification, and feature extraction/reduction on wine dataset.

This repository contains machine learning programs in the Python programming language.

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

PCA(Principle Component Analysis) For Wine dataset in ML

Wine Dataset with Gaussian Classifier

NTHU EE6550: Machine Learning

MSDS 410 Data Modeling for Supervised Learning (R)

Webscraping of Signorvino.com, an Italian wine e-commerce website. The task is performed with Selenium library in Python

This project implements two algorithms, K-Nearest Neighbors (KNN) and Large Margin Nearest Neighbor (LMNN) using the Neighbourhood Component Analysis (NCA) approach.

LDA(Linear discriminant Analysis) for Wine Dataset in machine learning

Store the exercises carried out in the discipline "Computing Inspired by Nature" of the PPGCC of UNESP.

web crawling tool to retrieve reviews from vivino.com website

Introducing Flask Program for wine Dataset

A New Support Vector Finder Method, Based on Triangular Calculations and K-means Clustering

GPT-3 wine recommendation website

Implementation of Hybrid fuzzy-rough Rule induction and feature selection paper 2009 by Richard Jensen