How to predict user next purchase items

Question

I have an e-commerce website where customers can purchase items directly from the site. I have training data which includes order id, user id, order number, days since prior order, product id, add to cart order, reordered...

I am trying to predict, for each user, what items he will purchase on his next order. I tried to use Naive Bayes, average purchase items per user and the following equation: posterior ~ Bayes Factor x prior but the prediction outcome is not good and has many false positives and/or negatives.

Maybe I can try to first train on the number of items a user will purchase then train on the specific items he will get but not sure will it get better results. I think this can go in the multi label classification but has not used multi labels in classification before.

I am using python with sklearn, pandas...

Any better models I can use and how to train and predict variable multi labels and whether I can do it in sklearn? Keep in mind that the data is large and predicting using some of the classification algorithms in sklearn unfortunately takes huge amounts of memory so, any ideas on how to reduce memory consumption would also be useful.