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stillworkin t1_ixs09pm wrote

I'll extend this: for the majority of real computer science/ engineering work (especially back-end stuff), *nix is the way to go. It's a huge reason Macs are the standard for CS folks (ever since the terminal became part of the MacOS). At every university I attended and taught, and at every company I've worked for, linux/macs have been used by essentially 100% of the people. Roughly once a year I'll hear/see someone using Windows.

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RichardBJ1 t1_ixs8fsy wrote

Macs for deep-learning?

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ryuks_apple t1_ixsgcr9 wrote

Just as an ssh box into your linux server

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RichardBJ1 t1_ixtsp1x wrote

Yes I have a few Macs and do that all the time! …Really I was replying In the context of the OP post however…. setting up a new system for DL.

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ryuks_apple t1_ixtsszd wrote

You can use macs for most toy problems in university too, but otherwise yeah...

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Appropriate_Ant_4629 t1_ixtlme6 wrote

Yes

https://towardsdatascience.com/installing-pytorch-on-apple-m1-chip-with-gpu-acceleration-3351dc44d67c

>> Installing PyTorch on Apple M1 chip with GPU Acceleration

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RichardBJ1 t1_ixtsdc5 wrote

Thanks, I hadn’t seen that implementation, I ran some deep learning models on TensorFlow adapted for iMac GPU, but it was less stable and significantly slower than the Nvidia Linux/Windows equivalents. Things have moved on I guess.

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