Coursera Project Network의 Interpretable Machine Learning Applications: Part 1 학습자 리뷰 및 피드백
In this 1-hour long project-based course, you will learn how to create interpretable machine learning applications on the example of two classification regression models, decision tree and random forestc classifiers. You will also learn how to explain such prediction models by extracting the most important features and their values, which mostly impact these prediction models. In this sense, the project will boost your career as Machine Learning (ML) developer and modeler in that you will be able to get a deeper insight into the behaviour of your ML model. The project will also benefit your career as a decision maker in an executive position, or consultant, interested in deploying trusted and accountable ML applications.
Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions....
Interpretable Machine Learning Applications: Part 1의 2개 리뷰 중 1~2
교육 기관: Pascal U E
2021년 7월 1일
I was looking for this content for very long time, I will finish all the series. Keep doing great guided projects.
교육 기관: Venkataramana M
2022년 8월 7일
Pretty Informative and crisp to the point. Great hands on course.