logoalt Hacker News

throwaway2027today at 4:34 AM7 repliesview on HN

I don't think these are useful at all. If you implement a simple network that approximates 1D functions like sin or learn how image blurring works with kernels and then move into ML/AI that gave me a much better understanding.


Replies

socalgal2today at 7:10 PM

Agree. They didn't seem to convey any info what-so-ever, pretty as they were

noduermetoday at 11:19 AM

Idk, it's fun. 20 years ago I made a cubic neural model in Flash that actually lit up cubes depending on how much they were being accessed. This was a case of binding logic way too tightly to display code, but it was a cool experiment.

ameliustoday at 4:52 PM

Yes, especially if you ask someone why one is better than the other in a certain configuration.

barrenkotoday at 5:04 AM

Yup, I'd say you learn more by doing math by hand (shouldn't be that surprising).

show 1 reply
patreshtoday at 9:15 AM

They're likely of limited use for someone looking for introductory material to ML, but for someone having done some computer vision and used various types convolution layers, it can be useful to see a summary with visualizations.

nobodywillobsrvtoday at 8:56 AM

Thank you for saying this. I often find this "glib" explains of ML stuff very frustrating as a human coming from an Applied Math background. It just makes me feel a bit crazy and alone to see what appears to be a certain kind of person saying "gosh" at various "explanations" when I just don't get it.

Obviously this is beautiful as art but it would also be useful to understand how exactly these visualizations are useful to people who think they are. Useful to me means you gain a new ability to extrapolate in task space (aka "understanding").

j45today at 1:36 PM

Learning first principles of something are always useful for beginners.

Everyone is a beginner at something.