Agree with previous posts re: reading papers being potential rabbit hole for NLP practitioners. One paper that could be pretty useful for practical applications

Agree with previous posts re: reading papers being potential rabbit hole for NLP practitioners. One paper that could be pretty useful for practical applications is this one https://arxiv.org/pdf/1904.12848.pdf https://arxiv.org/pdf/1904.12848.pdf It outlines strategies for data augmentation in NLP, as well as other ML task. Finding task-specific labeled data is often one of the most pertinent issues for applying ML outside of academia.