Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
612-822-4611

  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Predictive Viticulture: A Machine Learning Approach to Wine Quality

Predictive Viticulture: A Machine Learning Approach to Wine Quality

Siraj, Imran
Batra, Reenu
Balhara, Ritika

Paperback

General Sociology

ISBN10: 6630168879
ISBN13: 9786630168877
Publisher: LAP Lambert Academic Publishing
Published: Jul 3 2026
Pages: 72
Weight: 0.24
Height: 0.17 Width: 6.00 Depth: 9.00
Language: English
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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General Sociology

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