Assignments and Supplemental Reading Materials
Explore key papers on word embeddings such as GloVe and improved word vectors to deepen your understanding. Learn to build word2vec models that measure sentence similarity using cosine similarity, and create 100-dimensional word vectors with gensim. Complete assignments that reinforce concepts and prepare you for advanced NLP projects.
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Now that you have built a project and completed the quiz, you are ready to move on to the next step: exploring supplemental reading materials and completing the provided assignments to better understand the topics we discussed.
Supporting reading materials
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GloVe: Global Vectors for Word Representation by Jeffrey Pennington, Richard Socher, and Christopher D. Manning. This is the original paper that introduced the GloVe embeddings. If you skip this ...