Transforming Input Features for Machine Learning
In the realm of machine learning, the adage “garbage in, garbage out” holds true. The quality of your input often determines the quality of your output. One of the pivotal steps in prepping data for machine learning models is feature engineering. Feature engineering is akin to preparing ingredients for a dish. The better the preparation, […]