I think too many people feel held back from doing a project like thing on their own.
Absolutely. Also, too many people don’t feel held back enough (e.g. maybe it really would have been beneficial to, say, go through Spinning Up in Deep RL before attempting a deep RL project). How do you tell which group you’re in?
This is a good point, although I suppose you could still think of this in the framing of “just in time learning”, i.e. you can attempt a deep RL project, realise you are hopelessly out of your depth, then you know you’d better go through Spinning Up in Deep RL before you can continue.
Although the risk is that it may be demoralising to start something which is too far outside of your comfort zone.
you can attempt a deep RL project, realise you are hopelessly out of your depth, then you know you’d better go through Spinning Up in Deep RL before you can continue.
Tbc, I do generally like the idea of just in time learning. But:
You may not realize when you are hopelessly out of your depth (“doesn’t everyone say that ML is an art where you just turn knobs until things work?” or “how was I supposed to know that the algorithm was going to silently clip my rewards, making all of my reward shaping useless?”)
You may not know what you don’t know. In the example I gave you probably very well know that you don’t know RL, but you may not realize that you don’t know the right tooling to use (“what, there’s a Tensorboard dashboard I can use to visualize my training curves?”)
Both of these are often avoided by taking courses that (try to) present the details to you in the right order.
Yep, always tricky here. I was actually just reading Reversing Advice just before posting this but wasn’t sure how I should manage this.
Advice is like medication.It should come with similar rules, regulations, restrictions and warnings.
Some advice is over the counter and can be used by almost everyone. Advice should be used in moderation, do not take more than the recommended dose. Prescription medicine is illegal to advertise for (in Australia) because it is not useful for everyone and should only be recommended by a health care professional. Some advice does not mix well with other advice and care should be taken when mixing advice. Do not take advice that has been recommended to someone else as it may not apply to you. A particular problem may have several different advice that is helpful for it but each does not work for everyone, so you may need to try a few before you find the one that works for you.
Having said that I think I would default to aiming for the higher thing when you are not sure. If you aim high you may fall short and if you aim low you can still only fall short. So if you’re on the margin, start with a deep RL project. You might quickly find that its hard to do and fall back to doing Spinning Up.
If symptoms persist, please consult your health care professional.
Absolutely. Also, too many people don’t feel held back enough (e.g. maybe it really would have been beneficial to, say, go through Spinning Up in Deep RL before attempting a deep RL project). How do you tell which group you’re in?
(This comment inspired by Reversing Advice)
This is a good point, although I suppose you could still think of this in the framing of “just in time learning”, i.e. you can attempt a deep RL project, realise you are hopelessly out of your depth, then you know you’d better go through Spinning Up in Deep RL before you can continue.
Although the risk is that it may be demoralising to start something which is too far outside of your comfort zone.
Tbc, I do generally like the idea of just in time learning. But:
You may not realize when you are hopelessly out of your depth (“doesn’t everyone say that ML is an art where you just turn knobs until things work?” or “how was I supposed to know that the algorithm was going to silently clip my rewards, making all of my reward shaping useless?”)
You may not know what you don’t know. In the example I gave you probably very well know that you don’t know RL, but you may not realize that you don’t know the right tooling to use (“what, there’s a Tensorboard dashboard I can use to visualize my training curves?”)
Both of these are often avoided by taking courses that (try to) present the details to you in the right order.
I feel like I’m on both sides of this, so I’ll take the fast.ai course and then immediately jump into whatever seems interesting in PyTorch
Yep, always tricky here. I was actually just reading Reversing Advice just before posting this but wasn’t sure how I should manage this.
Advice is like medication. It should come with similar rules, regulations, restrictions and warnings.
Some advice is over the counter and can be used by almost everyone. Advice should be used in moderation, do not take more than the recommended dose. Prescription medicine is illegal to advertise for (in Australia) because it is not useful for everyone and should only be recommended by a health care professional. Some advice does not mix well with other advice and care should be taken when mixing advice. Do not take advice that has been recommended to someone else as it may not apply to you. A particular problem may have several different advice that is helpful for it but each does not work for everyone, so you may need to try a few before you find the one that works for you.
Having said that I think I would default to aiming for the higher thing when you are not sure. If you aim high you may fall short and if you aim low you can still only fall short. So if you’re on the margin, start with a deep RL project. You might quickly find that its hard to do and fall back to doing Spinning Up.
If symptoms persist, please consult your health care professional.
(See response to rory_greig above)