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Explores the aim and process of batch normalization in deep neural networks, emphasizing its importance in stabilizing mean input and solving the vanishing gradient problem.
Explains the full architecture of Transformers and the self-attention mechanism, highlighting the paradigm shift towards using completely pretrained models.
Explores environmental computational science and earth observation through accurate deep learning models for monitoring, integrating domain knowledge in species models, and enhancing image search.
