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

In today's data-driven environment, Python has become the mainstream language in the fields of machine learning and data science due to its concise syntax, rich library support, and active community, ...

Traditional machine learning methods like Support Vector Machines, Random Forest, and gradient boosting have shown strong performance in classifying device behaviors and detecting botnet activity.

Importantly, explainable AI is beginning to be integrated into these systems, offering pathways to clarify how models reach their conclusions. This emerging focus on interpretability is seen as ...