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How many hours do you think this course would take for an experienced developer with plenty of applied maths but ~no machine learning? How easy is it to do the

by mkl 4y ago

How many hours do you think this course would take for an experienced developer with plenty of applied maths but ~no machine learning? How easy is it to do the course on my own hardware rather than cloud notebooks? Would that make it closer to practical deployment?

gandalfgreybeer 4y ago
Not him nor will I talk about his course, but I’ve been in the field a reasonable amount of time (both on the academia and industry side). Honestly, applied maths will get you a long way and make it easier to digest the concepts (you might just see them as repackaged problems depending on your mileage). If you have good programming skills and discipline you practically have most of what you need. Re the course, I just skimmed it and I think you can do most things on your own hardware but if you will actually use this for something practical (not just for you or a side project), being familiar with cloud tools is a big thing especially once you scale.
- qwrshr 4y ago
  out of curiosity, how much applied math should one bone up on? (Obviously the more the better, but diminishing marginal returns and all that.)
  - cinntaile 4y ago
    None, just look things up as you go along if there is something you don't understand. You're likely not going to bother understanding how the optimization functions work or how the cost functions actually work anyway. They're implementation details in most cases.
  - gandalfgreybeer 4y ago
    Bare minimum is basic calculus, basic linear algebra and basic statistics. By basic, I probably mean first courses for those in most undergraduate programs. I disagree with needing none and just going along as needed. That’s how you have machine learning models that look like they work but you don’t understand why they work so there might actually be problems.
    - cinntaile 4y ago
      That's not quite what I said. I said to look things up if you don't understand, I made the assumption that the one asking has taken maths courses before. I interpreted bone up on as refreshing old knowledge but I could be wrong.
jph00 4y ago
I'd suggesting budgeting about 80 hours for the course given that background. That should get you to a place where you can work on practical projects that are reasonably well within standard applications of deep learning. Most practical deployment is done to cloud environments rather than local notebooks. The deployment exercise we do in the course is designed to show the key components you'll need for deploying simple models in practice.

by mkl 4y ago

gandalfgreybeer 4y ago

Not him nor will I talk about his course, but I’ve been in the field a reasonable amount of time (both on the academia and industry side). Honestly, applied maths will get you a long way and make it easier to digest the concepts (you might just see them as repackaged problems depending on your mileage). If you have good programming skills and discipline you practically have most of what you need. Re the course, I just skimmed it and I think you can do most things on your own hardware but if you will actually use this for something practical (not just for you or a side project), being familiar with cloud tools is a big thing especially once you scale.

qwrshr 4y ago
out of curiosity, how much applied math should one bone up on? (Obviously the more the better, but diminishing marginal returns and all that.)
- cinntaile 4y ago
  None, just look things up as you go along if there is something you don't understand. You're likely not going to bother understanding how the optimization functions work or how the cost functions actually work anyway. They're implementation details in most cases.
- gandalfgreybeer 4y ago
  Bare minimum is basic calculus, basic linear algebra and basic statistics. By basic, I probably mean first courses for those in most undergraduate programs. I disagree with needing none and just going along as needed. That’s how you have machine learning models that look like they work but you don’t understand why they work so there might actually be problems.
  - cinntaile 4y ago
    That's not quite what I said. I said to look things up if you don't understand, I made the assumption that the one asking has taken maths courses before. I interpreted bone up on as refreshing old knowledge but I could be wrong.

jph00 4y ago

I'd suggesting budgeting about 80 hours for the course given that background. That should get you to a place where you can work on practical projects that are reasonably well within standard applications of deep learning. Most practical deployment is done to cloud environments rather than local notebooks. The deployment exercise we do in the course is designed to show the key components you'll need for deploying simple models in practice.