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In todays video, we are going to talk about tokenization in spaCy. We can do tokenization in NLTK as well. We have discussed the pros and cons between these two libraries and, we decided well use spaCy for the reasons I mentioned in the last video. And if you remember our NLP pipeline video, we had this uh this step called pre-processing. So in this entire NLP pipeline, were going to begin with the pre-processing step. The data acquisition and text extraction and cleanup step is something we can maybe take a look at later, maybe in the end-to-end NLP project. But in pre-processing what we learned was, there is a step called sentence tokenization, when you you have a paragraph of text. You first separate it out in sentences and then each sentence you split it out in the into the words. So thats called word tokenization. So we are going to see how you can do both of these things in spaCy library. Also, there was stemming, lemmetization well cover stemming, lemmetization in the late