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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Principales reseñas sobre SUPERVISED 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
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.
Great course and very well structured. I'm really impressed with the instructor who give thorough walkthrough to the code.
This course is has a detailed explanation on each and every aspect of classification.
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