Compare feature ranges and assess scaling needs

Calculate the min, max, and mean for all 13 features (e.g., alcohol, residual sugar, sulfur dioxide). Create a visual summary (like a boxplot) and write a short paragraph explaining why neural networks are particularly sensitive to unscaled tabular data.

Start by locating the notebook and dataset containing the 13 features, including alcohol, residual sugar, and sulfur dioxide. Calculate each feature's minimum, maximum, and mean, add a visual summary such as a boxplot, and finish with a short explanation of why neural networks are sensitive to unscaled tabular data.

Written by the indexing model from the issue text.