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NCA-ADS - Data Manipulation and Preparation - Section 1.2

Handle data cleaning and data quality.

Identify and resolve common data quality issues including missing values, duplicates, outliers, and inconsistent types. Choose appropriate imputation or removal strategies based on the distribution and downstream model requirements.

More in this domain

Integrate, join, and manipulate data using cuDF and pandas.Section 1.1
Build GPU-accelerated ETL workflows.Section 1.3
Apply feature engineering.Section 1.4
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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