So is Software Engineering for Data Scientists/ML Engineers.
Machine Learning Is Still Too Hard for Software Engineers
11–20 of 112 posts
Re: Machine Learning Is Still Too Hard for Software Engineers
#12Do you have recommendations for good books that are not too mathematical, written for the average developer?
https://fleuret.org/francois/lbdl.html
There's a 0-60 in 3 seconds one. Specifically about deep learning, which is a subset of ML. Deep learning is what is used to build LLMs ala ChatGPT.
Re: Machine Learning Is Still Too Hard for Software Engineers
#13It's hard because it's useless, but overhyped.
You're forced to solve problems with inappropriate tools, which is an anathema for a true engineer.
Same as it was with NFTs and where they are?
Same as it is with clouds and k8s;
Re: Machine Learning Is Still Too Hard for Software Engineers
#14I feel so validated by this article. I took two semesters of machine learning electives for my CS masters and feel nearly as ignorant and mystified as when I started. I worked so hard to create something useful and at the end of the day, my work felt like it was 96% example code with modifications hacked in to make it work. And in the end it was still terrible! At least now I know what people are talking about when discussing neural nets and their inner mechanics.
For now, ML research and development is too complicated and frustrating for me to dedicate the time and energy to become skilled in it.
Re: Machine Learning Is Still Too Hard for Software Engineers
#15ML is one of the easiest fields out there. When I learned it I was actually turned off by how simplistic the concept was. Of course let me preface to say that it's hard to develop the intuition and skill in the same way learning to skateboard is hard. But conceptually it's easy and very possible for almost anyone. The whole thing is just curve fitting. Literally finding some best fit curve across a series of points.…
Can I get a link to anything about this crisis? My evening popcorn lulzsession demands...
Re: Machine Learning Is Still Too Hard for Software Engineers
#16As a software engineer, I disagree. Caveat, I haven't studied traditional ML and just went straight to DL. There is a lot of jargon and you do have to sit down and learn how things work, but once you do, deep learning is fairly simple. One thing that actually really bothers me is how much libraries (e.g. huggingface) are just config files masquerading as programming. It is just a class with 50 parameters and takes about 5 lines of code to make it do the thing, most of the time is spent figuring out what the parameters do.
I think making lower level tools (fundamental building blocks) will make things more accessible to software engineers, as opposed to the high level wrappers being written. We can grab a library, read the docs, and put pieces together in an efficient way. We just need some core work horse libraries. Like if llama.cpp was a library at the same maturity as sqlite.
Re: Machine Learning Is Still Too Hard for Software Engineers
#17ML is one of the easiest fields out there. When I learned it I was actually turned off by how simplistic the concept was. Of course let me preface to say that it's hard to develop the intuition and skill in the same way learning to skateboard is hard. But conceptually it's easy and very possible for almost anyone. The whole thing is just curve fitting. Literally finding some best fit curve across a series of points.…
"It is difficult to get a man to understand something, when his salary depends on his not understanding it." (Upton Sinclair)
Re: Machine Learning Is Still Too Hard for Software Engineers
#18ML is a broad topic, and it keeps getting wider, and deeper. Even ML specialists don't try to keep up with it all. Be comfortable with not knowing everything. Machine learning engineers are software engineers, and they exist, so the title is wrong. I suppose it is in Nyckel's interest to claim otherwise.
The industry has been consolidating around transformers. I'd say it's getting deeper, not wider.
Re: Machine Learning Is Still Too Hard for Software Engineers
#19[deleted]
Re: Machine Learning Is Still Too Hard for Software Engineers
#20I was a software engineer for ten years before going back to school for a statistics degree. In my experience, I thought very deterministically, and that really got in the way of interpreting the mathematical concepts that are, by definition, stochastic. Engineers think in IF statements. ML thinks in probabilities. This is a nontrivial mental barrier to overcome.
It doesn’t help that a lot of engineers want to find shortcuts that involve not learning the math. That’s just more engineering thinking. Not all disciplines throw exceptions when the output is bad. Maybe there will be tools that negate this need some day. I have yet to see them.