Feature engineering involves systematically transforming raw data into meaningful and informative features (predictors). It is an indispensable process in machine learning and data science.

Learn More. I spoke with Razi Raziuddin, CEO of FeatureByte, about the best way to prep data for ML models; he also explained some of the most common challenges with feature engineering.

With their object detection approach, they combined region-based CNNs with active learning and transfer learning to enable detection of the small defects using training sets of only 500 to 2,500 ...