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Challenge: Scaling the Features | Preprocessing Data with Scikit-learn
ML Introduction with scikit-learn
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Conteúdo do Curso

ML Introduction with scikit-learn

ML Introduction with scikit-learn

1. Machine Learning Concepts
2. Preprocessing Data with Scikit-learn
3. Pipelines
4. Modeling

book
Challenge: Scaling the Features

In this challenge, you need to scale the features using StandardScaler. The data is the penguins dataset (encoded and with no missing values).

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import pandas as pd df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/a65bbc96-309e-4df9-a790-a1eb8c815a1c/penguins_imputed_encoded.csv') print(df)
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Here is a little reminder of the StandardScaler class.

Tarefa
test

Swipe to show code editor

  1. Import the class that standardizes features by making the mean equal to 0 and the variance equal to 1.
  2. Initialize the scaler.
  3. Scale the X matrix of features.

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Tudo estava claro?

Como podemos melhorá-lo?

Obrigado pelo seu feedback!

Seção 2. Capítulo 11
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book
Challenge: Scaling the Features

In this challenge, you need to scale the features using StandardScaler. The data is the penguins dataset (encoded and with no missing values).

12345
import pandas as pd df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/a65bbc96-309e-4df9-a790-a1eb8c815a1c/penguins_imputed_encoded.csv') print(df)
copy

Here is a little reminder of the StandardScaler class.

Tarefa
test

Swipe to show code editor

  1. Import the class that standardizes features by making the mean equal to 0 and the variance equal to 1.
  2. Initialize the scaler.
  3. Scale the X matrix of features.

Switch to desktopMude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
Tudo estava claro?

Como podemos melhorá-lo?

Obrigado pelo seu feedback!

Seção 2. Capítulo 11
Switch to desktopMude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
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