Mastering the Machine: ML for the Real World explores the practical challenges and strategies for implementing machine learning systems beyond controlled research environments. While academic ML often focuses on clean datasets and benchmark accuracy, real-world applications must deal with messy, incomplete, and constantly evolving data. The book emphasizes that success in production ML is less about achieving the highest model accuracy and more about building systems that are scalable, reliable, interpretable, and aligned with business goals. Key themes include the importance of data quality and preprocessing, as most real-world effort goes into cleaning, balancing, and engineering features rather than model selection alone. The text highlights data drift, concept drift, and feedback loops, showing how models degrade over time without proper monitoring and retraining. It also covers model evaluation, stressing that accuracy is insufficient for imbalanced datasets and that fairness, interpretability, and business KPIs must guide decision-making. Overall, the work positions machine learning as not just a technical challenge but a socio-technical system requiring collaboration among data scientists, engineers, and domain experts.
外文書商品之書封，為出版社提供之樣本。實際出貨商品，以出版社所提供之現有版本為主。部份書籍，因出版社供應狀況特殊，匯率將依實際狀況做調整。
無庫存之商品，在您完成訂單程序之後，將以空運的方式為你下單調貨。為了縮短等待的時間，建議您將外文書與其他商品分開下單，以獲得最快的取貨速度，平均調貨時間為1~2個月。
為了保護您的權益，「三民網路書店」提供會員七日商品鑑賞期(收到商品為起始日)。
若要辦理退貨，請在商品鑑賞期內寄回，且商品必須是全新狀態與完整包裝(商品、附件、發票、隨貨贈品等)否則恕不接受退貨。
