Run a notebook to generate a word embedding model such as www.tensorflow. org/text/guide/word_embeddings, which trains an embedding model based on a corpus of IMDB movie reviews. Create the embedding model and visualize the embeddings. Then create another model based on a different text corpus and compare. What similarities and differences do you notice? If you are not able to run a notebook, you can compare five different pre-built word embeddings at vectors.nlpl.eu/explore/embeddings/en/associates/.