I've been working with language technology in some capacity for over a decade now, and in that time I've noticed a pretty consistent pattern of mistakes made by technologists *especially* if they're new to working with language data. Whether you're a software engineer moving into a new domain, or a student using machine learning for the first time, it's likely that you will probably make at least one if not more of these mistakes unless someone helps you avoid it. And that's why this document exists: to help you learn what the common mistakes are how to avoid them. (Also includes a handy checklist you can print out and keep handy.)