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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- 5 stars88,43 %
- 4 stars10,40 %
- 3 stars0,57 %
- 1 star0,57 %
Principales reseñas sobre SUPERVISED MACHINE LEARNING: CLASSIFICATION
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
This course is has a detailed explanation on each and every aspect of classification.
Great course, well structured. The presentation of the different methods is very clear and well separated to understand the differences. A good understanding of classifiers is gained from this course.
this course taught me a lot even after being a practioner for 10+ years!
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