this post was submitted on 27 Nov 2023
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Machine Learning
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Right, that's why OP prefaced with "to dive deeper into a lot of the topics". If folks aren't at a point where diving deeper makes sense, it's not a list for them. There are plenty of resources for any given level of understanding, obviously no list is going to be appropriate for every member of a diverse community.
Not to start an argument here but I can't imagine anybody with any level of understanding who should start diving deeper by reading the "Attention is All You Need" paper. Yes, this is a diverse community, but when you try to address everybody's needs, you usually end up with addressing nobody's needs.
Since "Attention is All You Need" is fairly high on my reading list for understanding the details of transformer architecture, what do you recommend instead?
https://arxiv.org/abs/2106.04554
If you're trying to learn more about language models don't bother with anything written before 2020. That's basically the Stone Age.
Thank you!