I don't how to explain this, but when I see you, I see a German Senior C++ Engineer for some reason
Instructions unclear : Bought an AMD Rx 7900XT
Also for doing neural networks the GPU is not always needed, I was playing with a small model and then I tried the computer of my brother's to see if I could speed up everything with the GPU and it wasn't faster.
well it depends on the complexity of the task. suppose you’re working on time series forecasting, you could do that with either scikit or tf/pytorch which are ML or DL respectively. by following the tf/pytorch approach you may get better results due to the NNs, but this approach demands heavy requirements like CUDA for parallel computations and accelerate the process. Meanwhile, if you are satisfied with slightly worse and cardinal results, you could just stick to ML which don’t demand much
Thank you 🙏 really helpful ❤❤❤
Tremendo trabajo de investigación, gracias por tomarte el tiempo para recopilar toda esta información y resumirla.
A smooth balance for me is about ram:gpu. 12-15:1 for each gb gpu 12 gb ram
Please a video how we apply ML to earthquake data set.
My man out here looking beautifull fr
for gpu's unless you're a deep learning guy with loaded pockets, it is not worth it to buy some rtx laptop or something with low vram, simply because these things require a LOT of computing, the free kaggle gpus are better in that regard
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can i connect like 8 bad cpu´s? and train with that?
Do I need upgrade my Gtx 1660Ti GPU?
Was he on GoT?. Good answer.
you dont need one!!!!!
Ya right... I spent 8 hours training on the cpu for a CLASSIC ML model, I don't think you have that much of experience in the ai field
Can I do Ho 15 s
Agreed!
It’s between a 6700 XT Radeon and a 4060 TI Nvidia card. I want to game and be able to train fast on my pc. 😫
@ordinarypablo