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.
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來自 SUPERVISED MACHINE LEARNING: CLASSIFICATION的熱門評論
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
The course content is very great in the coding area and it is very helping. but a shortage that is clear is the theory behind every algorithm, the handling of it wasn't that much perfect.
The course is very well structured, and the explanations very clear. I would only suggest enhancing the peer-review community since it takes a long time to get a review sometimes.
I would like to give especial thanks to the instructor (the one in the videos) for his great job. It would be nice to know who is is.