Data Science, Machine Learning, NLP, Transformers, Word Embeddings.
if_exists='ignore') # English ft = fasttext.load_model('cc.en.300.bin') Create an embedding for the word ‘king’. ft.get_word_vector('king') Get most similar words for the word ‘king’. ft.get_nearest_neighbors('king') Test model ability to create vectors for unknown words. 'king-warrior' in ft.words