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This project is about the prediction of red wine quality using different machine learning algorithms
This Repository Contains different Machine Learning Projects on various dataset. From Exploratory Data Analysis - Visualization to Prediction and Classification..
Data Science Projects done at Data Trained Education during PG Data Science & ML Course
Hello friends, I am making a Machine Learning repo. where I will upload several datasets and its solution with explanation. Starting from the basic and moving up in difficulty level.
A visualization of the dataset winequality-red.csv and exploratory data analysis[ EDA ] in R language
Wine Quality Classification using KNN, SVM, and Random Forest
Exploratory Data Analysis (EDA) is the numerical and graphical examination of data characteristics and relationships before formal, rigorous statistical analyses are applied.
You will likely perform tasks like removing duplicates, handling missing values, and consistently formatting data. Data analysis and visualization: Data analysts play a key role in analyzing data to uncover insights and trends.
These datasets can be viewed as classification or regression tasks. The classes are ordered and not balanced (e.g. there are much more normal wines than excellent or poor ones).
This repository stored the output of IBM SPSS's multiple linear regression and factor analysis of red wine quality dataset. The dataset used is from Kaggle (https://www.kaggle.com/uciml/red-wine-quality-cortez-et-al-2009). The software used in this repository is IBM SPSS 26
This project is about the prediction of red wine quality using different machine learning algorithms with MLOps and CICD pipeline.
I implemented the Random Forest Algorithm, from the scratch, to predict the quality of red wine. The algorithm proved to be quite accurate.
Repository for diffrent solutions of Kaggle classification competitions
This project endeavors to predict wine quality through machine learning, unraveling the intricate factors influencing wine characteristics.
This project is about the prediction of red wine quality using different machine learning algorithms
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