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Exploring Self-Supervised Learning Techniques
This chapter focuses on self-supervised learning, emphasizing the importance of data cleaning and augmentation to enhance training datasets. It examines contrastive and non-contrastive learning methods, highlighting innovations and challenges in maximizing data representation while maintaining key characteristics.