Reading through that ebook I mentioned in my previous post, I’m once again reminded that machine learning is an experimental science. The general approach to solving a problem is to throw everything at it and see what works best. And by ‘everything’ I mean multiple variations of multiple algorithms within multiple families, plus a few ensemble solutions for dessert.
That’s a lot of processing. My most powerful PC is out of action. It has an RTX2080Ti graphics card which, while a bit old now, is still well regarded for ML processing. I’m thinking of building a new machine. In the past I’ve had a couple of machines built by friends who are more hardware savvy than I am, including the Linux box I’m currently using. Over the years I have built a lot of different things (not computers), some of them quite challenging. It should be easy.
So, build a dedicated ML PC. It won’t be for a while because I still have so much to learn. And I’m getting older. Maybe it will happen one day. Or perhaps I can just get someone to do a custom buiid for me. Do I really need to do it myself? I’m getting to that stage in my life where it’s easier just to pay someeone else to do things for me. Pity.
Reading a bit further, Jason suggest cloud-based resources, such as AWS. Perhaps I should give that serious consideration.