Feature Engineering for Machine Learning
Feature Engineering for Machine Learning Feature engineering is the process of turning raw data into features that help a model learn patterns. Good features can lift accuracy, cut training time, and make models more robust. The work combines data understanding, math, and domain knowledge. Start with clear goals and a plan for what signal to capture in the data. Before building models, clean and align data. Handle missing values, fix outliers, and ensure consistent formats across rows. Clean data makes features reliable and reduces surprises during training. ...