5olidor

5 ms·

1.
by 5olidor 10y ago
It seems like reinforcement learning would be useful, i.e. at a high level, forming a policy for recommendations would require balancing exploration (experimenting with more risky recommendations) vs. exploitation (showing you recommendatio
2.
by 5olidor 10y ago
Apostol's calculus texts were my first experience with 'real' proof-based mathematics, and I also learned real analysis through his Mathematical Analysis book. Good times; his books taught me a lot. He wrote with clarity and
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by 5olidor 10y ago
On the probability side, I thought Ash's "Probability & Measure Theory" was good for self-study, although some experience with real analysis is definitely a prerequisite. It can be pretty dense at times, but well worth go
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by 5olidor 11y ago
I like the observation about the importance of concentration. In addition to reading, I've noticed that studying mathematics is an opportunity to practice (or build) the ability to focus on frustratingly difficult material that require
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by 5olidor 11y ago
That makes sense, thanks
6.
by 5olidor 11y ago
Agreed, I was just curious since some of the comments below seemed to imply that PhDs / PostDocs lack certain software development skills (although I personally haven't seen this). If so, this would either suggest that the code qu
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by 5olidor 11y ago
Does this also apply to large industrial labs, e.g. MSR, IBM Research, Google research etc.? Or are there software developers who work together with researchers in those places, perhaps resulting in better quality code?