Use a linear regression model. Perform one-hot encoding on categorical features, and create additional features based on the date, such as day of the week or month.

Use a boosted tree model. Perform label encoding on categorical features, and transform the date column into numeric values.

Use an autoencoder model. Perform label encoding on categorical features, and normalize the date column.

Use a matrix factorization model. Perform one-hot encoding on categorical features, and create interaction features between the store location and product category variables.