Stop Feeling Lost :  How to Master ML System Design

A comprehensive framework for mastering machine learning system design is presented as a crucial skill for advancing a career in data science. The process is broken down into key stages: defining the business problem, data acquisition, feature engineering, model design, deployment, and monitoring. Necessary theoretical knowledge in ML and practical skills in system engineering, like cloud services and containerization, are also detailed. The guide concludes with advice for preparing for ML system design interviews and provides a list of learning resources.