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Hello and welcome to this art tutorial.

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So now, in this new
step of the cleaning process,

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we will remove all the punctuations
in the reviews of the corpus.

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And it's going to be as simple as before.

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We will copy this line, paste

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it below
and instead of remove numbers here

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we will input remove punctuation.

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As simple as that.

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We don't need anything else.

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And that's ready to remove any punctuation
and all the reviews of the corpus.

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All right so let's check it out.

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We can actually check it out
with the first review.

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Well it's really all that love this place.

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And so what we're supposed to obtain
after applying this remove

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punctuation function and all the reviews
of the corporate through the tmp function.

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Well, the three little dots
are supposed to disappear.

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All right. So let's check it out.

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So remember in the actual version
of the corpus right now,

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the first review is wow, thrilled
that I love this place.

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So now let's select this new line of code,

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execute new corpus of reviews
created with all the punctuation removed.

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So let's go back to the console
and let's press the up arrow to get

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the line of code that is giving us access
to the first review.

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Here it is. So let's press enter now.

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And as you can see, the thrilled
that's disappeared.

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Therefore that's exactly what the remove
punctuation function does here.

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It removes any kind of punctuation,
including dot commas.

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Collins.

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Semicolon
or any other kind of punctuation.

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All right.

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So next step done.

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We are ready to move on to the next step,

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which will be to remove
all the non relevant words in the reviews.

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So for example if we have a look at this
first review here.

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Well this is not very relevant.

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You know this doesn't give any hint on
knowing whether the review is positive

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or negative.

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So this is typically a word that we don't
want to have in the final sparse matrix

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because this is not relevant.

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So we will remove it in the next step
of the cleaning process.

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And we'll do the same
for all the other words of the same kind.

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So let's do that in the next tutorial.

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And until then enjoy machine learning.