Understand data preprocessing techniques essential for preparing raw data for analysis and machine learning. Learn how to clean, transform, and standardize data to improve analysis accuracy.
Topics Covered
Introduction: Importance of cleaning and transforming raw data.
Data Preprocessing Techniques: Handling missing values, scaling, encoding, and dimensionality reduction.
Example in Python: Demonstrating imputation, normalization, and encoding with libraries like Pandas and Scikit-learn.
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Master data preprocessing with hands-on examples and exercises tailored to your needs.
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