LAP LAMBERT Academic Publishing

Predictive Viticulture: A Machine Learning Approach to Wine Quality

Name: Predictive Viticulture: A Machine Learning Approach to Wine Quality
Brand: LAP LAMBERT Academic Publishing
SKU: 243882753172952a7957f11988474dfc

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Afbeelding van Predictive Viticulture: A Machine Learning Approach to Wine Quality

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47,99

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	47,99	Naar shop
	69,82	Naar shop
	69,82	Naar shop
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Beschrijving

Bol In this project, a Wine Quality Prediction System was developed to predict the quality of wine based on various physicochemical properties. The system leverages Python programming and the Scikitlearn library for implementing machine learning algorithms. A Random Forest Classifier was employed to achieve accurate and efficient predictions. The project utilizes Pandas and NumPy for data preprocessing and exploratory data analysis, while Matplotlib and Seaborn were used for visualization of trends and patterns in the dataset. The dataset used for this project was sourced from the UCI Machine Learning Repository. The development process followed the Iterative life cycle model of software development, ensuring systematic implementation and testing of features. The project is structured using Modular Design Principles, enhancing maintainability and scalability.

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€ 69,82 € 4,21 verzendkosten Totaal € 74,03

Beschrijving (1)

In this project, a Wine Quality Prediction System was developed to predict the quality of wine based on various physicochemical properties. The system leverages Python programming and the Scikitlearn library for implementing machine learning algorithms. A Random Forest Classifier was employed to achieve accurate and efficient predictions. The project utilizes Pandas and NumPy for data preprocessing and exploratory data analysis, while Matplotlib and Seaborn were used for visualization of trends and patterns in the dataset. The dataset used for this project was sourced from the UCI Machine Learning Repository. The development process followed the Iterative life cycle model of software development, ensuring systematic implementation and testing of features. The project is structured using Modular Design Principles, enhancing maintainability and scalability.

Lees meer