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I am a beginner in Tensorflow. I am working on a dataset for sentiment analysis. I have used two kinds of methods one is LSTM and the other is LSTM with pre-trained word embeddings like (GloVe & Fast Text). I can see there is a difference of accuracy. But can anyone explain what are the advantages of working with pre-trained word embeddings with LSTM over just LSTM.

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