the A.I. from SYNTHESPIAN

Practical Machine Learning — Practical Machine Learning

Practical Machine Learning — Practical Machine Learning — Read on c.d2l.ai/stanford-cs329p/

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Tesla AI day

Tesla Dojo has GPU compute, more IO than the highest end networking chips, and flexibility! It uses a novel system on wafer (InFO_SoW) for an order magnitude higher performance vs Nvidia, Graphcore, Cerebras, Groq, Tenstorrent, SambaNova, etc. https://t.co/VJwS3MjNWH

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Curs DL de la NYU

https://atcold.github.io/pytorch-Deep-Learning/?s=09

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Becoming a Data Scientist

https://www.kdnuggets.com/2020/02/data-science-curriculum-self-study.html?s=09

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Curs DL en català

https://deeplearning.telecos.upc.edu/courses/aa2?s=09

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Deep Learning course

I'm releasing all the lectures (so far) for my deep learning class, CS182! This is an introductory deep learning course (advanced undergraduate + graduate) covering a broad range of deep learning topics. Website: https://t.co/0PaBOJElo9Playlist: https://t.co/21GvfFRcHo 🧵-> — Sergey Levine (@svlevine) March 13, 2021

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New version

Thanks for the feedback, everyone! Below is a slightly extended version based on all the awesome responses I received. Will probably extend it some time with more concrete methods for some of the categories some time later this semester 🙂 pic.twitter.com/p3budoESWB — Sebastian Raschka (@rasbt) March 10, 2021

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Pytorch 1.8 en GPUs AMD

That's a great release! – AMD GPU support via ROCm (binaries available directly from the installer menu)– Now possible to fit large models onto GPUs w/o external libraries: pipeline and model parallelism– determinants & eigenvalues via torch.linalg w/o switching to NumPy https://t.co/3QN8wxCN0W — Sebastian Raschka (@rasbt) March 5, 2021

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Duck-Rabbit illusion

twitter.com/stevestuwill/status/1366501252964573184

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