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Welcome to Machine Learning with Imbalanced Datasets. In this course, you will learn multiple techniques which you can use with imbalanced datasets to improve the performance of your machine learning models.
If you are working with imbalanced datasets right now and want to improve the performance of your models, or you simply want to learn more about how to tackle data imbalance, this course will show you how.
We’ll take you step–by–step through engaging video tutorials and teach you everything you need to know about working with imbalanced datasets. Throughout this comprehensive course, we cover almost every available methodology to work with imbalanced datasets, discussing their logic, their implementation in Python, their advantages and shortcomings, and the considerations to have when using the technique. Specifically, you will learn:
Under–sampling methods at random or focused on highlighting certain sample populations
Over–sampling methods at random and those which create new examples based of existing observations
Ensemble methods that leverage the power of multiple weak learners in conjunction with sampling techniques to boost model performance
Cost sensitive methods which penalize wrong decisions more severely for minority classes
The appropriate metrics to evaluate model performance on imbalanced datasets
By the end of the course, you will be able to decide which technique is suitable for your dataset, and / or apply and compare the improvement in performance returned by the different methods on multiple datasets.
Specification: Machine Learning with Imbalanced Data
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7 reviews for Machine Learning with Imbalanced Data
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| Price | $10.99 |
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| Provider | |
| Duration | 11.5 hours |
| Year | 2022 |
| Level | Intermediate |
| Language | English ... |
| Certificate | Yes |
| Quizzes | No |
Hj –
Easy to follow, systematic and very user friendly.
R P –
There are lot of mistakes in formulas, it forced to refer the same topic in another forum to completely understand the concept.
Wiffer Sekhutle Mosehla –
great course
Yean Yik Y Yong –
It’s very clear, and goes indepth into each topic. the course is pretty exhaustive and is very helpful in pointing the uninitiated to the right direction.
Carlos Andr s Campo Gonz lez –
As always, awesome teacher makes a great job. I can implement this in my job today. Great.
Pitabas Mohanty –
Very useful course.
Danxu688 –
Very good course, well prepared, very clear explanation and nice demo. The instructor knows how to teach, what students need to know and hands on practice, etc. I have taken 3 courses of her. I think what I learned from her will be helpful for the data scientist job.