July 2017
Beginner to intermediate
486 pages
13h 49m
English
Content preview from Python Natural Language Processing
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Post-processing
Post processing is a kind of rule-based system. Suppose you are developing a machine translation application and your generated model makes some specific mistakes. You want that machine translation (MT) model to avoid these kinds of mistakes, but avoiding that takes a lot of features that make the training process slow and make the model too complex. On the other hand, if you know that there are certain straightforward rules or approximations that can help you once the output has been generated in order to make it more accurate, then we can use post-processing for our MT model. What is the difference between a hybrid model and post-processing? Let me clear your confusion. In the given example, I have used word approximation. ...
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