This course is designed to equip learners with a foundational understanding of the essential metrics and techniques used to evaluate machine learning models. Participants will explore various performance metrics such as accuracy, precision, recall, F1-score, ROC-AUC, and more, while gaining insights into when and why each metric is appropriate. Through practical examples and real-world scenarios, this course will enable learners to confidently assess model performance, identify potential issues, and make informed decisions about model improvements.
Clouder certification:
https://edu.alibabacloud.com/clouder/exam/intro/887
