Machine Learning classification problem displayed with Flask Application
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Updated
Jun 21, 2022 - Python
Machine Learning classification problem displayed with Flask Application
Building classification models to predict quality of wines. (Accuracy = 71.33%)
Wine Predicts
Predicting wine quality using machine learning
Predicting the quality of a good bottle of wine
Classification of wine quality using a hard_parzen and a soft_parzen with gaussian kernel models - Machine Learning course (IFT3395)
This project is designed to predict the quality of red or white wine based on various features. It utilizes Streamlit for the user interface and incorporates machine learning models from scikit-learn.
Example data-science web application, from "Hello, World!" to app
K means clustering implementation on the wine quality dataset
Using Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) on same dataset and analyzing the best one
ML algorithms for Regression, Classification, Clustering and Dimensional Reduction applied in a Wine Quality Dataset.
Predict wine quality using a machine learning model (Random Forest) served with FastAPI. Includes containerization with Docker and monitoring via Prometheus and Grafana.
Wine-quality has been predicted through supervised learning using regression and classification models.
A feedforward neural network to predict wine quality based on a number of scientific factors. NOTE: This is purely an educational project. This is neither an efficient nor realistic neural network for commercial use.
Having fun with MLOPS: Wine Stuff
In this project I did lot of efforts because the dataset used was imbalanced that's why i couldn't find any ML algorithms that gave me good results, I tried different Sampling techniques, although nothing happened. Finally I build this project using ANN and got an 77% accuracy and also very good precision, recall and f1 score.
We're going to use some models to predict the Datasets and show the predictions results in a table.
A neural network for wine quality prediction
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