3 ms·

Coming from a background in computational quantum chemistry, it’s interesting to see all of the people who say ML is “easy” after taking a few online courses an

Coming from a background in computational quantum chemistry, it’s interesting to see all of the people who say ML is “easy” after taking a few online courses and reading some books on data science. If it’s so easy, invent AGI then, since that is the holy grail of machine learning. Most of these people claiming expertise do not have a deep grasp of the mathematical fundamentals required for state of the art research in the field. Can you develop a neural network with features that are invariant to permutational and rotational symmetries? If so, how do you efficiently generate the irreproducible representations of the product of the symmetric and special orthogonal groups for use in a fast Fourier transform? What is minimum description length and why is it so fundamental? How do you solve trust-region problems on Riemannian manifolds? Throwing an off-the-shelf PyTorch library at a problem does not make one an expert in machine learning.

uejfiweun 5y ago
Not to disagree with your point, but your comment really reminded me of the following scene from Breaking Bad: https://www.youtube.com/watch?v=W_dxteeedgs https://www.youtube.com/watch?v=W_dxteeedgs
- Xcelerate 5y ago
  Haha, I’d never seen that. I suppose my comment is a bit over-the-top compared to my comment history, but it’s somewhat of a touchy point for me when someone jumps into a new field and claims it’s easy and that they’re an expert without being able to back up the claim (some rare people can do this with a new field; most cannot).
  - antifa 5y ago
    Is it though? When I run the hello world for whatever GAN or pytorch, what exactly am I going to do if I get an unexpected error message? Or if the results are off? Would I even know the results are off? I don't even know if pytorch is used for GAN.
    - p1esk 5y ago
      You’re going to do exactly what any decent SWE would do - debug it. But of course, if you don’t know what you’re doing then you gotta learn first. Plenty of resources out there on how GANs work.
JBits 5y ago
What does representation theory and Fourier transforms have to do with neural networks (I've not properly studied ML)?
- Xcelerate 5y ago
  In the majority of cases, not much. My point is more that many people who claim expertise in machine learning do not have a holistic understanding of the field; their knowledge is patchy and they aren’t able to implement a solution to more than the most general of problems. It would be like a car mechanic that can change the oil but doesn’t know how to locate and fix a leak. Most neural networks that perform well nowadays are highly specialized to a particular problem domain, and I gave an example of an approach that might be used by someone designing a neural network that is invariant to certain types of symmetries on the input data. This isn’t something a typical DS/ML bootcamper would know how to handle, or even how to approach, despite their claims of expertise.

uejfiweun 5y ago

Not to disagree with your point, but your comment really reminded me of the following scene from Breaking Bad: https://www.youtube.com/watch?v=W_dxteeedgs https://www.youtube.com/watch?v=W_dxteeedgs

Xcelerate 5y ago
Haha, I’d never seen that. I suppose my comment is a bit over-the-top compared to my comment history, but it’s somewhat of a touchy point for me when someone jumps into a new field and claims it’s easy and that they’re an expert without being able to back up the claim (some rare people can do this with a new field; most cannot).
- antifa 5y ago
  Is it though? When I run the hello world for whatever GAN or pytorch, what exactly am I going to do if I get an unexpected error message? Or if the results are off? Would I even know the results are off? I don't even know if pytorch is used for GAN.
  - p1esk 5y ago
    You’re going to do exactly what any decent SWE would do - debug it. But of course, if you don’t know what you’re doing then you gotta learn first. Plenty of resources out there on how GANs work.

JBits 5y ago

What does representation theory and Fourier transforms have to do with neural networks (I've not properly studied ML)?

Xcelerate 5y ago
In the majority of cases, not much. My point is more that many people who claim expertise in machine learning do not have a holistic understanding of the field; their knowledge is patchy and they aren’t able to implement a solution to more than the most general of problems. It would be like a car mechanic that can change the oil but doesn’t know how to locate and fix a leak. Most neural networks that perform well nowadays are highly specialized to a particular problem domain, and I gave an example of an approach that might be used by someone designing a neural network that is invariant to certain types of symmetries on the input data. This isn’t something a typical DS/ML bootcamper would know how to handle, or even how to approach, despite their claims of expertise.