Exploring the potential of self-supervised learning in advanced AI models for improved adaptability and efficiency. Seeking insights on methodologies and applications from the ResearchGate community.
Dear S M Mohiuddin Khan Shiam ,
Self-supervised learning holds paramount importance in the field of artificial intelligence due to its ability to alleviate the dependency on labeled data. In domains where labeled data is scarce or expensive to obtain, self-supervised learning offers a viable solution for training effective models.
https://www.larksuite.com/en_us/topics/ai-glossary/self-supervised-learning
Regards,
Shafagat
Dear S M Mohiuddin Khan Shiam ,
Self-supervised learning holds paramount importance in the field of artificial intelligence due to its ability to alleviate the dependency on labeled data. In domains where labeled data is scarce or expensive to obtain, self-supervised learning offers a viable solution for training effective models.
Self-supervised learning stands as a groundbreaking paradigm that has garnered significant attention and acclaim. This transformative approach to machine learning has demonstrated remarkable potential by enabling machines to learn directly from raw, unlabeled data, surpassing traditional supervised learning methods in certain scenarios. Self-supervised learning embodies the essence of autonomous learning, allowing AI systems to extract meaningful representations and patterns from data without explicit human annotations.
https://www.linkedin.com/pulse/self-supervised-learning-artificial-intelligence-arastu-thakur-dvryc/
Regards,
Shima Shafiee
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