How do I group similar categories?
Use a pre trained model to generate embeddings, and from there you can cluster the embeddings using a clustering algorithm like t-SNE or UMAP. I recommend fasttext or spacy, with spacey being the easiest to use.
I have about 1200 tv show categories .. like Drama, News, Sports, Sports-non event, Drama Medical, Drama Crime.. etc
How do I use NLP so that I get groups such that Drama, Drama medical and Drama Crime group together and Sports, Sports-non event etc group together and so on... basically the end goal is to reduce the 1200 categories to very few broad categories.
Till now I have used bag of words to build a dictionary with 146 words..