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@@ -13,6 +13,9 @@ Taking a probabilistic approach to deep learning allows to account for uncertain
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  **Full credits go to [Khalid Salama](https://www.linkedin.com/in/khalid-salama-24403144/)**
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  ## Training and evaluation data 🍷
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  We use the wine quality dataset found [here](https://www.tensorflow.org/datasets/catalog/wine_quality). Each wine was scored from 0-10 by wine experts, and includes 11 physicochemical features about the wine.
 
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  **Full credits go to [Khalid Salama](https://www.linkedin.com/in/khalid-salama-24403144/)**
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+ ## Using this model
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+ This repo contains model weights only. To use this model, refer to the following code contained in load_bnn_model.py.
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  ## Training and evaluation data 🍷
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  We use the wine quality dataset found [here](https://www.tensorflow.org/datasets/catalog/wine_quality). Each wine was scored from 0-10 by wine experts, and includes 11 physicochemical features about the wine.