Implementation of various ML algorithms and their application to real world problems
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Updated
Mar 28, 2020 - Jupyter Notebook
Implementation of various ML algorithms and their application to real world problems
Wine Quality Prediction
A continuous Machine Learning integration workflow using Github Actions. This project is based upon team collaboration for aesthetic version control for ML pipelines and deployement.
Predicting the quality of Wine
Wine Quality Prediction Model (ML) ExtraTreesClassifier 88% Accuracy
This repository includes ml model of 1.House price prediction using linear regression model | 2.Wine Quality prediction using linear regression model | 3. IRIS Flowers Classification using logistic regression model
Predicting quality of white wine using chemical attributes
A wine quality prediction machine learning model 🍷📈 uses data to assess and forecast the quality of wines, aiding wine enthusiasts and producers in making informed choices. 🤖👍🍇
Implemented back-propagation algorithm on a neural network from scratch using Tanh and ReLU derivatives and performed experiments for learning purpose
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.
Train a neural network to predict the quality of red-wine using chemical properties such as pH, density, alcohol percentage etc.
K means clustering implementation on the wine quality dataset
CPC152 Foundations and Programming for Data Analytics [AY 21/22]]
ML algorithms for Regression, Classification, Clustering and Dimensional Reduction applied in a Wine Quality Dataset.
ANN model which predicts wine quality
This was the final project for the Machine Learning course.
This repository contains projects completed during Data Science Internship at CodeClause.
Empowering Advanced Text Classification and Wine Quality Prediction with Cutting-Edge Machine Learning Techniques.
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