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Exp 11

The document outlines a project aimed at predicting wine quality using machine learning techniques based on a dataset of wine characteristics. It emphasizes the importance of understanding factors influencing wine quality for better production and consumer choices. The project involves collecting data and building a predictive model for wine quality assessment.

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rehanp009900
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5 views4 pages

Exp 11

The document outlines a project aimed at predicting wine quality using machine learning techniques based on a dataset of wine characteristics. It emphasizes the importance of understanding factors influencing wine quality for better production and consumer choices. The project involves collecting data and building a predictive model for wine quality assessment.

Uploaded by

rehanp009900
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
Available Formats
Download as PDF, TXT or read online on Scribd
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EXPERIMENT NO-11

AIM- Wine Quality prediction

Theory –
Problem definition –

Wine quality assessment is crucial for winemakers, sommeliers, and consumers. Understanding the factors that
influence wine quality can lead to better production processes and informed choices for consumers. Machine
learning techniques can help predict wine quality based on various features.
The goal of this project is to predict the quality of wine based on a set of input features. We will use a dataset
containing information about different wines and their associated quality ratings.

Implementation:
Conclusion:

In this project, we addressed the task of predicting wine quality using data science and machine learning. We
began by collecting the Wine Quality Dataset, which contains essential features related to wine characteristics.
Our objective was to build a model capable of assessing wine quality based on these features.

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