Data silos are isolated collections of data within an organization that are not easily accessible by other teams or systems, hindering collaboration and unified data analysis.
CatBoost is a machine learning gradient-boosting library that builds decision trees optimized for handling categorical data with high accuracy and minimal data preprocessing.
Data labeling is the process of annotating raw data with meaningful tags or classifications so machine learning models can learn to recognize patterns and make accurate predictions.
Object-relational mapping (ORM) is a programming technique that lets developers use object-oriented code to interact with relational databases, by translating objects to and from database-compatible formats.
