Self-Supervised Learning
Simon and Tim discuss the power of self-supervised pre-training for creating semantically relevant representations in computer vision. They delve into the importance of data augmentation and the minimal role architecture plays in contrastive learning, highlighting the key insights in SIM CLR paper.In this clip
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Machine Learning Street Talk (MLST)
#032- Simon Kornblith / GoogleAI - SimCLR and Paper Haul!
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