Preprocessing techniques are crucial steps in data preparation that enhance the quality of data for analysis and machine learning models, ensuring more accurate and efficient results. These techniques involve cleaning, transforming, and organizing raw data into a structured format suitable for analysis, addressing issues like missing values, noise, and inconsistencies.

Preprocessing Techniques

Preprocessing techniques

data preparation

quality of data

analysis and machine learning models

accurate and efficient results

Cleaning raw data

Transforming Raw Data

organizing raw data

structured format

missing values

Noise in data

Inconsistencies in data

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