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Python 3
Data Preprocessing

Data Preprocessing

Data Preprocessing

Data Preprocessing

Raw datasets often require preprocessing before they can be used for machine learning.

Data preprocessing improves data quality and prepares the dataset for training.

Typical preprocessing steps include:

Checking missing values
Removing duplicate records
Verifying data types
Separating input and target variables
Scaling numerical features

Proper preprocessing helps improve model performance and ensures consistent results.

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Data Preprocessing

Contents

Data Preprocessing

Credit Card Fraud Detection for Beginners using Data Science

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