A language model can predict the probability of the next word in the sequence, based on the words already observed in the sequence.Neural network models are a preferred method for developing statistical language models because they can use a distributed representation where different words with similar meanings have similar representation and because they can use a large context of recently observed words when making predictions.
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A language model can predict the probability of the next word in the sequence, based on the words already observed in the sequence.Neural network models are a preferred method for developing statistical language models because they can use a distributed representation where different words with similar meanings have similar representation and be…
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A language model can predict the probability of the next word in the sequence, based on the words already observed in the sequence.Neural network models are a preferred method for developing statistical language models because they can use a distributed representation where different words with similar meanings have similar representation and be…
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