Highlights:
* (semi-)supervised topic modeling
* Added Spacy, Gensim, USE (TFHub)
* Use a different backend for document embeddings and word embeddings
* Create your own backends with `bertopic.backend.BaseEmbedder`
* Calculate and visualize topics per class
Fixes:
* Fixed issues with Torch req
* Prevent saving term frequency matrix in CTFIDF class
* Fixed DTM not working when reducing topics (#96)
* Moved visualization dependencies to base BERTopic
* `pip install bertopic[visualization]` becomes `pip install bertopic`
* Allow precomputed embeddings in bertopic.find_topics() (#79)