A basic program to get overview to the overview of the quality of red wine

The data is coming from https://www.kaggle.com/zynicide/wine-reviews and it's a massive dataset of wines reviews with information as the professional description, price, points and so on. The aim of the project is to give an overview of a worldwide wine clues, for example, the relation between price and quality(points), the countries where the wines are made or perform an analisys of the most used words to decrive wines. The future lines of this analisys could be to implement a Machine Learning algorithm to predict the clues(aroma,taste) that corresponds to an exellent wine.

Improving wine quality using machine learning (ML) involves leveraging data-driven techniques to analyze various factors influencing wine production and consumer preferences. This approach can significantly enhance the consistency, taste, and overall quality of wine. Here's an overview of how ML can be utilized in this context:

OIBSIP_DataAnalytics_Task2 Wine Quality dataset

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Project Overview: The session involved a repository named "wine" with a Kaggle dataset on red wine properties and quality ratings. The project's goal was to predict wine quality ratings using various features.

Wine Quality Dashboard Overview A Power BI Dashboard that analyzes wine quality based on chemical properties like acidity, alcohol content, and residual sugar. The interactive visuals and filters help explore patterns and correlations, offering insights for wine producers and enthusiasts. Features Interactive filters for wine type and quality.

📌 Project Overview Wine quality assessment is traditionally performed by expert tasters, which can be subjective and time-consuming. This project aims to predict the quality of wine based on its physicochemical properties using machine learning techniques