This depends quite a lot on the domain. In some image processing tasks you can actually be cpu-bound during dataloading. So either you get tons of RAM and preload the dataset, or you use more cores to queue up batches. You still need a good GPU and generally I'd agree to prioritise that first.
You can get CPU bound, I am $100 under and you could put money towards that or RAM. I did also leave a path to upgrade RAM. But that said, I've been working with image generation a lot lately and CPU really isn't my bottleneck.
If doing image processing (or NLP with rec nets), I wouldn't save on VRAM. 11GB minimum (2080/1080TI). Otherwise you can't even run the bigger nets with good image resolution.
