Fundamentals of Dask Transcripts
Chapter: Dask-ML
Lecture: Checkpoint 2

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0:00 All right, everybody now it's time for a check point. We've just seen how to use Dask-ML. in order to generalize the scikit-
0:08 learn API. And code and algorithms to out of memory data sets So now it's your turn to use dask-ml to do the same with a
0:16 "Naive Bayes classifier" on the given data set. So we've seen it with k-nearest neighbors and also with logistic regression.
0:24 Now you can do it with a Naive Bayes classifier. If you want to know a bit more about that,
0:29 you can check out the scikit-learn resources either by googling it or clicking on the
0:33 hyperlink here. So what we're going to get you to do is put your answer
0:36 in there and of course always respect distributed data science hygiene by closing the cluster afterwards


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