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In this video, I tell you everything you need to know about building your own machine learning workstation! Should you build it? How to do proper research on the components, which websites to use, how to buy components, and much more.
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Disclaimer: below are affiliate links - by clicking & buying I earn a percentage at no additional cost to you! :)
Core components:
* RTX 3090 [ Ссылка ]
* AMD Ryzen 9 7950x [ Ссылка ]
* ARCTIC Liquid Freezer II 280 [ Ссылка ]
* Asus ROG Crosshair X670E Hero [ Ссылка ]
* Kingston Fury Beast [ Ссылка ]
* Samsung 980 PRO 2 TB m.2 [ Ссылка ]
* SAMSUNG 870 QVO SATA III 8TB [ Ссылка ]
* Lian Li PC-O11DW 011 DYNAMIC [ Ссылка ]
* EVGA Supernova 1600 G+ [ Ссылка ]
Peripherals I use (super happy with my decision esp. keyboard!):
* Dell U2720Q UltraSharp 27 Inch 4K [ Ссылка ]
* Corsair K70 RGB MK.2 Mechanical w/ MX brown [ Ссылка ]
* Mouse: Corsair M65 PRO RGB [ Ссылка ]
List: [ Ссылка ]
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Blogs I recommended in the video:
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⌚️ Timetable:
00:00 Intro - announcing the new series
02:00 Why should you build your deep learning workstation?
03:56 Quick skim of the components
04:45 pcpartpicker is your friend
07:20 Cost comparisons - Lambda Labs workstation & laptop, cloud
15:45 Researching the components - useful resources
15:57 Overview Tim Dettmers' blogs
19:20 Do you need 11+ GBs?
22:55 Don't follow someone's advice blindly!
27:08 Upgrade to NVIDIA 40x series?
28:05 Other resources
30:30 How to pick the right components?
32:10 CPU - Ryzen 9 7950x or Threadripper?
33:50 CPU Cooler
34:45 MoBo
37:50 Memory and storage
40:40 Case
42:00 PSU
42:55 Quick mention of my peripherals
43:15 Advice for targeting your particular budget
44:25 Tips for buying components - site aggregators, Amazon, legitness
48:25 Outro
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💰 BECOME A PATREON OF THE AI EPIPHANY ❤️
If these videos, GitHub projects, and blogs help you,
consider helping me out by supporting me on Patreon!
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Huge thank you to these AI Epiphany patreons:
Eli Mahler
Petar Veličković
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#deeplearning #machinelearning #workstation #rig #pc #build
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