Web Reference: Nov 8, 2025 · Feature Engineering is the process of selecting, creating or modifying features like input variables or data to help machine learning models learn patterns more effectively. It involves transforming raw data into meaningful inputs that improve model accuracy and performance. Jan 9, 2023 · The goal is to ensure that the data is of high quality and relevance to the problem being addressed and to continually improve the data set through data cleaning, feature engineering and data augmentation. Responsibility: 1. Generate meaningful features from existing data. 2. Use techniques like PCA or feature importance to select the most important features. 3. Optimize feature sets for improved model performance. - hetkthakkar/MainFlow-Task-5
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