macORnvidia
macORnvidia OP t1_j0xw1kp wrote
Reply to comment by sayoonarachu in laptop for Data Science and Scientific Computing: proart vs legion 7i vs thinkpad p16/p1-gen5 by macORnvidia
How's the performance in deep learning and data science in general
I'm fine with 12th gen too. Cost not an issue. Just want an overall elite product
macORnvidia OP t1_iv8ssle wrote
Reply to comment by arhetorical in bought legion 7i: Intel i9 12th gen, rtx 3080 ti 16 gb vram, 32 GB ddr5. need some confirmation bias (or opposite) to understand if I made the right decision by macORnvidia
>An external GPU will just make your setup less portable without actually giving you the performance of a workstation
Can you please elaborate?
Also, as for training, I get it, I can't really train deep learning models but how about optimizing machine learning models using pyCUDA?
macORnvidia OP t1_iv8l6za wrote
Reply to comment by arhetorical in bought legion 7i: Intel i9 12th gen, rtx 3080 ti 16 gb vram, 32 GB ddr5. need some confirmation bias (or opposite) to understand if I made the right decision by macORnvidia
Still under that 15 day period. I wanted to get my hands on a machine instead of constantly wondering. What should I look out for to basically validate or discredit my decision over the next week?
Say if it comes to returning it, I'd be down to buying a 32 gb laptop without gpu, but a desktop gpu that I can plug n play and use accordingly.
macORnvidia OP t1_j0z24ie wrote
Reply to comment by sayoonarachu in laptop for Data Science and Scientific Computing: proart vs legion 7i vs thinkpad p16/p1-gen5 by macORnvidia
>. For example, the largest Parque file I've cleaned in pandas was about 7 million rows and about 10gb in size of just text. It can run queries through it in a few seconds.
Using rapids? Like cudf?