This course introduces you to one of the main types of modeling families of supervised Machine Learning: Classification. You will learn how to train predictive models to classify categorical outcomes and how to use error metrics to compare across different models. The hands-on section of this course focuses on using best practices for classification, including train and test splits, and handling data sets with unbalanced classes.
이 강좌에 대하여
귀하가 습득할 기술
- 5 stars89.09%
- 4 stars9%
- 3 stars0.94%
- 1 star0.94%
SUPERVISED MACHINE LEARNING: CLASSIFICATION의 최상위 리뷰
Great! Helps me build my career path in Data Science
Superb ,detailed, well explained, lots of hands on training through labs and most of the major alogrithms are covered!
Keep up the good work. You guys are helping the community a lot :D
Great course and very well structured. I'm really impressed with the instructor who give thorough walkthrough to the code.
The course is well designed and easy to follow. (communication and feedback mechanism with Coursera could be improved).