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NCA-ADS - Data Manipulation and Preparation - Section 1.4

Apply feature engineering.

Create informative input features through encoding, scaling, binning, and interaction terms to improve model predictive power. Recognise which transformations are appropriate for categorical versus continuous variables in an accelerated pipeline.

More in this domain

Integrate, join, and manipulate data using cuDF and pandas.Section 1.1
Handle data cleaning and data quality.Section 1.2
Build GPU-accelerated ETL workflows.Section 1.3
Handle class imbalance.Section 1.5
Apply dimensionality reduction.Section 1.6
Use Parquet storage for data.Section 1.7

Back to all Data Manipulation and Preparation objectives, or the NCA-ADS cert hub.

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