From the course: AWS Certified Generative AI Developer - Professional (AIP-C01) Cert Prep

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Feature engineering

Feature engineering

From the course: AWS Certified Generative AI Developer - Professional (AIP-C01) Cert Prep

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Feature engineering

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Feature engineering. What is feature engineering? This is the process of selecting, transforming, creating, and extracting features used in building machine learning models. Before fitting data into a machine learning model, we need to carefully shape that data. And this is what feature engineering is all about. It's the art of turning raw data into the right inputs for your model. It's one of the most crucial steps in the data preparation process that directly affects model performance. Why feature engineering matters? Because good features is equal to better predictions. It helps reduce noise, improve accuracy, and speed up training. Let's explore the different tasks under feature engineering. First is Feature Selection, keeping what matters. This is where you pick the relevant variables for model training, in which your goal is to minimize noise and reduce overfitting, which will lower your model complexity and improve accuracy. The common techniques under this method is the Filter…

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