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Get more information and GitHub link: upaspro.com/four-strategies-to-enhance-transformers-in-sequential-event-part-two/
Curriculum learning is the most effective but simple approach to enhance network performance when the data is small.
very indepth video. Can you have more simple content that more people understand.
Interesting approach for data augmentation. is it similar to other noise injection (like for models, dropout)?
Good job. I can’t see much of improvement in the data augmentation, is there any reason it was stopped there
Get more information and GitHub link: upaspro.com/four-strategies-to-enhance-transformers-in-sequential-event-part-two/
Curriculum learning is the most effective but simple approach to enhance network performance when the data is small.
very indepth video. Can you have more simple content that more people understand.
Interesting approach for data augmentation. is it similar to other noise injection (like for models, dropout)?
Good job. I can’t see much of improvement in the data augmentation, is there any reason it was stopped there