What is the significance of feature engineering in the context of model deployme

What is the significance of feature engineering in the context of model deployment?

What is the significance of feature engineering in the context of model deployment?

Step 1: Understand that feature engineering is the process of selecting and transforming data features to improve model performance.
Step 2: Recognize that when a model is deployed, it will encounter new data that may be different from the training data.
Step 3: Realize that well-engineered features help the model make accurate predictions on this new data.
Step 4: Acknowledge that if the features are not properly engineered, the model may perform poorly in real-world situations.
Step 5: Conclude that effective feature engineering is essential for the model to adapt and maintain its accuracy after deployment.

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