intermediate
intermediate
Hands-on Approaches to Handling Data Imbalance
Machine Learning
3 courses
47 practices
6 hours
Master techniques for handling data imbalance in machine learning. Progress from data preparation and baseline modeling to advanced resampling, evaluation metrics, and specialized algorithms for imbalanced datasets to build robust, fair models.
Verified skills you'll gain
INTERMEDIATE
Coding and Data Algorithms
DEVELOPING
Machine Learning Model Development
INTERMEDIATE
Model Validation and Selection
Tools you'll use
Pandas
Python
Scikit-learn
