In this session, we showcase the power of machine learning in taking a large corpus of a foreign language text (we use the entire Wikipedia) and automatically learning word embeddings for that language.
This is typically the first key step in building natural language processing (NLP) solutions, such as text classification or topic modelling. You see how easy it is to apply the BlazingText algorithm built into Amazon SageMaker in order to process the entire contents of Wikipedia in this language and visualize the results. You then can apply these learnings to any language of your choice.
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