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 stars88,46 %
- 4 stars10,43 %
- 3 stars0,54 %
- 1 star0,54 %
Top-Bewertungen von SUPERVISED MACHINE LEARNING: 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.
Thank you Coursera.
Thank you IBM
Thank you to all instructors.
Great! Helps me build my career path in Data Science
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.
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