Introduction to Data Preprocessing
Importance of Data Quality
Stages of Data Preprocessing
Handling Missing Data
Imputation Techniques
Dropping Missing Values
Data Normalization and Scaling
Min-Max Scaling
Z-Score Normalization
Encoding Categorical Variables
One-Hot Encoding
Label Encoding
Feature Engineering Techniques
Creating New Features
Feature Selection Methods
Data Splitting Strategies
Train-Test Split
Cross-Validation Techniques
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