Feature engineering is crucial in machine learning as it directly impacts model performance. It involves selecting, modifying, or creating new features from raw data to improve the model's ability to learn patterns. Proper feature engineering can enhance the model's accuracy, reduce overfitting, and increase interpretability. By transforming variables into more relevant forms or creating new features, data scientists can better capture the underlying relationships in the data. It also helps in reducing computational complexity, leading to faster training times and better generalization. Learn more about feature engineering and other essential skills in a Data Science course in Kolkata at Uncodemy, where expert instructors guide you through the intricacies of data science.
What is the importance of feature engineering in machine learning models?
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