Conclusion

Explore the essential concepts and techniques covered throughout the course to address challenges posed by mislabeled and imbalanced datasets. Learn how to recognize data noise issues and apply practical strategies to enhance model accuracy and fairness. This lesson consolidates your skills for effective handling of imperfect real-world data in machine learning applications.