From the course: GenAI and Predictive AI Architecture Foundations
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The feature engineering module
From the course: GenAI and Predictive AI Architecture Foundations
The feature engineering module
- Feature engineering is an important part of an AI system's internal processing. It's essentially the process of applying knowledge of a domain problem to select and revise and even create the most meaningful and relevant features from a dataset. This is done to optimize the data specifically for the AI system's model. After the data pre-processing module has carried out its tasks, the data is made available to the feature engineering module for this purpose. This module then essentially optimizes the features so that the data can be as easily understood and processed by the model as possible. It does so by performing a range of tasks such as creating new features, transforming or augmenting existing features, extracting or deriving new features from hidden patterns within the data, and identifying which features to keep and which to omit. In addition to transforming the data based on domain knowledge, this module can also apply dimensionality reduction techniques. This is important…
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