*Neural networks for data science: lecture 7 is out* 👀 These slides are all you need! A concise introduction to attention-based models, including positional encodings, self-attention, and permutation equivariance. /n 🧵 https://t.co/GUowCcyZD1

Neural networks for data science: lecture 7 is out 👀 These slides are all you need! A concise introduction to attention-based models, including positional encodings, self-attention, and permutation equivariance. /n 🧵 https://t.co/GUowCcyZD1

- 12월 16, 2021

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*Neural networks for data science: lecture 7 is out* 👀 These slides are all you need! A concise introduction to attention-based models, including positional encodings, self-attention, and permutation equivariance. /n 🧵 https://t.co/GUowCcyZD1
— Simone Scardapane (@s_scardapane) Dec 15, 2021

*Neural networks for data science: lecture 7 is out* 👀 These slides are all you need! A concise introduction to attention-based models, including positional encodings, self-attention, and permutation equivariance. /n 🧵 https://t.co/GUowCcyZD1 https://twitter.com/s_scardapane/status/1471163789278126088 https://t.co/GUowCcyZD1 December 16, 2021 at 02:02AM

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Neural networks for data science: lecture 7 is out 👀 These slides are all you need! A concise introduction to attention-based models, including positional encodings, self-attention, and permutation equivariance. /n 🧵 https://t.co/GUowCcyZD1

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