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wine-analysis

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kochlisGit / Wine-Preference-Analysis

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The purpose of this work is the modeling of the wine preferences by physicochemical properties. Such model is useful to support the oenologist wine tasting evaluations, improve and speed-up the wine production. A Neural Network was trained using Tensorflow, which was later tuned in order to achieve high-accuracy quality predictions.

python data-science machine-learning neural-network chemistry tensorflow scikit-learn keras hyperparameter-optimization data-analysis wine hyperparameter-tuning interpretability regression-analysis feature-importance optuna regression-model wine-analysis physicochemical-properties shap-values
  • Updated Jul 17, 2022
  • Jupyter Notebook

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