Learn how to handle imbalanced data in Machine Learning. Data based approaches, algorithmic approaches and more!
Master key concepts and practical skills through structured learning modules. By completing this curriculum, you'll gain valuable expertise applicable to real-world scenarios.
Understand the underline causes of the Class Imbalance problem
Why it is a major challenge in machine learning and data mining fields
Learn the different characteristics of imbalanced datasets
Learn the state-of-the-art techniques and algorithms
Understand variety of data based methods such as SMOTE, ADASYN, B-SMOTE and many more!
This comprehensive Imbalanced Learning (Unbalanced Data) - The Complete Guide curriculum is designed to take you from foundational concepts to advanced implementation. Each module builds upon the previous, ensuring a structured learning path that maximizes knowledge retention and practical application.
Understand what you need to succeed in this course and determine if it's the right fit for your learning goals
What you need before starting this Imbalanced Learning (Unbalanced Data) - The Complete Guide course:
This course is perfect for:
Everything you need to know about this online course, from duration to certification
Course Instructor
Bassam Almogahed
Expert instructor with industry experience
Course Language
English
All materials in English
This online course offers comprehensive training with expert instruction, practical exercises, and a certificate of completion. Join thousands of students advancing their careers through quality online education.
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