Greg Brockman's blog[1] has few links on how he picked up ML. Another link at [2] describes the path Michal(blog's author) followed (though it's aligned to "how i got into ..."). Both these blogs walk through how they were able to get into the ML bits of things. They have bunch of links (ex: [3]).
I think it'll help if you can get a job at a company who's main focus is ML, you'll talk to folks who are doing research or solving problems using ML, you'll learn. If not, i hope these links help as folks there (people way smarter than me, a swe) had similar question and documented the steps they took to reduce the gaps in their understanding.
Great resources, especially Brockman's blog makes the experiences so much acceptable, knowing that even the top people had to struggle to get going in ML
This seems to be the case in bay area too. The person delivering the food is not the same person in the DoorDash app. It used to be rare before but not anymore. (sample size of 1, as recent as 2 days ago).
Faced the same. Then I un-liked all the pages (some chrome add-on), un-followed few groups and the feed is much better. Finally I can see humans and not just news/meme
I think it'll help if you can get a job at a company who's main focus is ML, you'll talk to folks who are doing research or solving problems using ML, you'll learn. If not, i hope these links help as folks there (people way smarter than me, a swe) had similar question and documented the steps they took to reduce the gaps in their understanding.
[1] - https://blog.gregbrockman.com/how-i-became-a-machine-learnin... [2] - https://agentydragon.com/posts/2023-01-11-how-i-got-to-opena... [3] - https://github.com/jacobhilton/deep_learning_curriculum