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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Habilidades que obtendrás
- 5 stars89,20 %
- 4 stars8,92 %
- 3 stars0,93 %
- 1 star0,93 %
Principales reseñas sobre SUPERVISED MACHINE LEARNING: CLASSIFICATION
this course taught me a lot even after being a practioner for 10+ years!
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.
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.
Thank you Coursera.
Thank you IBM
Thank you to all instructors.
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