This project focuses on identifying the best hyperparameters for modeling and predicting trends in food sales using a Multi-Layer Perceptron (MLP) neural network. The objective is to optimize the MLP model to achieve high predictive accuracy, enabling businesses to make informed decisions regarding inventory management and sales strategies.
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This project focuses on identifying the best hyperparameters for modeling and predicting trends in food sales using a Multi-Layer Perceptron (MLP) neural network. The objective is to optimize the MLP model to achieve high predictive accuracy, enabling businesses to make informed decisions regarding inventory management and sales strategies.
wulanov/python-foodsales-MLP-Hyperparameter-Tuning
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This project focuses on identifying the best hyperparameters for modeling and predicting trends in food sales using a Multi-Layer Perceptron (MLP) neural network. The objective is to optimize the MLP model to achieve high predictive accuracy, enabling businesses to make informed decisions regarding inventory management and sales strategies.
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