People vary quite a bit, so this may only apply to a subset of readers. It definitely applies to me. I learn by working backwards much better than by finding a path from basics to an end result.
Also, for a whole lot of topics, “learn X” or even “study X” is not a well-formed intent. There are often an incredibly wide range of activities you could undertake that seem to be leading to your goal(s), but are actually part of a completely different result that happens to share the same name “know X”.
Don’t attempt to study machine learning. Pick an outcome you want (perhaps building a LessWrong comment classifier), and study enough to get that done. Then pick another outcome, and do that.
Don’t attempt to study quantum mechanics. Instead, try to figure out why you should care about the many-worlds interpretation.
Don’t attempt to study machine learning. Pick an outcome you want … and study enough to get that done.
For the record, machine learning is a topic where (1) it’s easy to fool yourself with over-optimistic test result (2) it’s easy to waste months improving parts of a project which do not matter in the end . These problems are both mitigated (somewhat) by learning the foundations.
Not to say you wouldn’t learn a lot by just diving in. Diving in, then going back and figuring out what you were doing seems like it could be a good thing for many people.
People vary quite a bit, so this may only apply to a subset of readers. It definitely applies to me. I learn by working backwards much better than by finding a path from basics to an end result.
Also, for a whole lot of topics, “learn X” or even “study X” is not a well-formed intent. There are often an incredibly wide range of activities you could undertake that seem to be leading to your goal(s), but are actually part of a completely different result that happens to share the same name “know X”.
Don’t attempt to study machine learning. Pick an outcome you want (perhaps building a LessWrong comment classifier), and study enough to get that done. Then pick another outcome, and do that.
Don’t attempt to study quantum mechanics. Instead, try to figure out why you should care about the many-worlds interpretation.
This strikes me as terrible advice. You’re advising people to exclusively read filtered evidence on a topic they know nothing about.
For the record, machine learning is a topic where (1) it’s easy to fool yourself with over-optimistic test result (2) it’s easy to waste months improving parts of a project which do not matter in the end . These problems are both mitigated (somewhat) by learning the foundations.
Not to say you wouldn’t learn a lot by just diving in. Diving in, then going back and figuring out what you were doing seems like it could be a good thing for many people.