Hi everyone,
I learnt how to use DL method to deal with structure data in the course, and want to use the method to deal with this (challenge)[https://www.kaggle.com/c/recruit-restaurant-visitor-forecasting]. I just found that the kernels on LB would like to leverage all kinds statistics across different time frames to predict visitors, and am wondering is that appropriate to combine fast.ai structure data processing pipeline and LSTM in order to preventing tricky feature engineering ? Thanks.