Text classification again part 1

1) Task: Develop/employ a text-classification algorithm in Python or R that classifies items as (a) one of 5,837 8-digit product codes and (b) (separately) one of 5,427 6-digit product codes using a descriptive text field of one to ten characters. Description: We have a database of 8,385 textual descriptions of products that have been entered by humans. Each entry is connected to both an 8-digit and a 6-digit product code (as well as the official description of each 8-digit and 6-digit code), but the same product code can be used for multiple differing textual entries. We require a text-classification algorithm that probabilistically classifies each entry as a specific 8-digit code and (separately) a specific 6-digit code. The official description of each 8-digit and each 6-digit code can also be used if this will increase the accuracy of the predictions. This task requires tokenizing, stemming, and removing stop words. Similarly, several different algorithms may need to be used to improve precision. Output: Python scripts/algorithm(s) classifying documents into 8-digit and 6-digit product codes.