Hey, I am currently a senior software engineer working mainly with backend systems. As I have to work another 30 years or so, I cannot deny that ML knowledge is more and more important nowadays and will become even more in the future.
I do not think that just learning the current frameworks will do me any good in the long run. Understanding the math and tech under the frameworks seems important to me for future growth.
However, my last math class was yeeears ago. Now my time is limited.
Is there a suggested way to learn the basic math to understand current(!) ML trends?
> As I have to work another 30 years or so, I cannot deny that ML knowledge is more and more important nowadays and will become even more in the future.
I think you're confusing being a user of ML tools with being someone who works on ML tools/systems/products. The landscape of available tools has really changed in the past year; the landscape for working in the field hasn't really - there aren't significantly more jobs, it's not much better or worse, it's not a job that everyone will need to do some day, it's just an okay sub-field of software engineering and/or research.
Why? This feels like saying you want to learn assembly because you have no faith in C. Abstracted tools will be all there is someday soon, the amount of people working on the math side of things will probably be highly specialized. You could learn this stuff now, but you have to consider who you're up against and what you'd actually do with that knowledge. If you write your own LLM and custom accelerator, you're still building the same product as the guy who just calls the OpenAI API.