nlp

TF-IDF is the classic text-vectorization scheme and a fast check of whether you actually understand term-frequency times inverse-document-frequency, or just recite it. The signal is explaining why IDF kills common words. Here is the implementation.

Detecting the language of a string sounds trivial until the input is three words, mixes two languages, or is half code. A strong answer picks the model by latency budget, handles short text and code-switching, and returns calibrated confidence instead of a brittle single guess.