This, but without the implication it’s cheating. As someone who’s both a software engineer and trains ML models, choosing a language that’s commonly used for the general task area you’re tackling (ML or not) is very useful. If it’s popular for the task area you’ll have a lot of references for how to solve problems, you can find and use libraries designed and demonstrated for similar tasks, and yes, you can cut and paste code snippets.
Almost every language is capable of doing anything, and software engineers regularly use multiple languages in the course of their work. Libraries and support are a big deal in deciding which to use, and will often be more important than your personal language familiarity/preference.


There are ways to label data that aren’t just humans selecting from a word list. The quality of that labeling is then dependent on the quality of the process you use to create it, but that can be good enough that it has value. Sometimes it’s just starting from a known good/easy label and tracking the thing it’s attached to forward or backward in a video.