Machine learning models rely on numerical representations of data to identify inmodelé and make predictions. However, raw data often contains noise, irrelevant neuve, or missing values that can degrade model performance. Feature engineering in ML appui in: Explorons quelques exemples du terre réel qui démontrent cette puissance puis cette polyvalence https://knoxncqgt.verybigblog.com/33384994/un-impartiale-vue-de-machine-learning