Imbalanced Classification With Python (7-Day Mini-Course)
Last Updated on August 18, 2020
Imbalanced Classification Crash Course.
Get on top of imbalanced classification in 7 days.
Classification predictive modeling is the task of assigning a label to an example.
Imbalanced classification are those classification tasks where the distribution of examples across the classes is not equal.
Practical imbalanced classification requires the use of a suite of specialized techniques, data preparation techniques, learning algorithms, and performance metrics.
In this crash course, you will discover how you can get started and confidently work through an imbalanced classification project with Python in seven days.
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Let’s get started.
Imbalanced Classification With Python (7-Day Mini-Course)
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Who Is This Crash-Course For?
Before we get started, let’s make sure you are in the right place.
This course is for developers that may know some applied machine learning. Maybe you know how to work through a predictive modeling problem end-to-end, or at least most
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