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So below, we have done preprocessing for our classification dataset.

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Now let's learn how to train our modern in Python.

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But as you know, before training or model, we need to standardize our data.

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So we will use a standard scalar program from a Skillern or prepossessing to do standardizing.

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We will first create a sea object which will contain the standardization information, for a word,

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independent datasets.

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So we are creating a sea object.

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We are using Cendon is scalar function and we are using Daudt fake method of dysfunction.

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And we are giving our extreme dataset as our training dataset for this Ascender scalar.

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Now, using this sended is scalar.

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We are transforming our external data and expense data.

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And we are asserting this standardized data and to extend standard and x test standard.

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Now, to view this data, you can just.

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Execute this.

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Come on.

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First, I have to execute on the above commands, and then if I run this.

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You can see that now over duties, Senator, is.

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All the variables are almost falling, the same skills and the mean of all the variables is zero and

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the variance of all the variables is now equal to one.

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We can use this standardized data to create our models.