Ragib_Zaman

12 ms·

61.
by Ragib_Zaman 7y ago
I guess I was being ridiculously optimistic hoping for the 16 core chip to be around the $600 mark :(
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by Ragib_Zaman 7y ago
Sure, if you need to continually access the same values then you'd want to save them but whether you need to reuse the same values or just do a one off calculation, you still need to compute the value the first time in some way. For Fi
63.
by Ragib_Zaman 7y ago
Not to say anything about the central thesis of the post, but the two examples of how deeper mathematical knowledge can lead to better programming are just terrible examples. As someone whose background was originally mathematics and starti
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by Ragib_Zaman 7y ago
> That's a poor assertion because even if detivative-free algorithms weren't already a thing, there are a myriad of smoothing techniques that enable nondifferentiable objective functions to be approximated by differentiable fun
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by Ragib_Zaman 7y ago
You shouldn't view GA as a competitor to gradient descent. Whenever gradient descent applies to a problem, it'll probably be better than GA. But GAs are flexible and applicable to more problems, and can be used in conjunction with
66.
by Ragib_Zaman 7y ago
In a somewhat similar vein, I've always found it odd that engineering students commonly refer to themselves as engineers. I agree with much of the linked article and believe the title of engineer implies that one has already gone throu
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by Ragib_Zaman 7y ago
I didn't mean you were the one implying an elementary proof is unobtainable, that was directed at some of the other replies to your comment like "oh really?". I agree that it's enlightening to give these things a try.
68.
by Ragib_Zaman 7y ago
Man HR is harsh as hell. While yes, if a proof of RH is found it will probably use advanced tools, ever finding a proof with elementary tools is not totally out of the question. Regarding the Prime Number Theorem, which can be seen as a bab
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by Ragib_Zaman 7y ago
Good practitioners do both. Whatever knowledge about the weights you can predetermine, you set those as the initial values of your weights. Then you improve on that by training. It really depends on the problem and size of your network how
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by Ragib_Zaman 7y ago
Perhaps not at the hardware level, I'm not sure. I downloaded InSpectre (a windows application) which informs me that I had been protected against Spectre and Meltdown attacks through Windows updates. I also used the option to disable
71.
by Ragib_Zaman 7y ago
I turn Spectre/Meltdown protection off (download InSpectre if you run Windows). My Haswell machine gets a noticeable boost (e.g. about 5% increase in Intel XTU benchmark), but newer architectures are less negatively affected by the pat
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by Ragib_Zaman 7y ago
People sometimes talk about waiting for a Spectre "fix" at a hardware or software level, but it seems that the only fix is to lose Speculative execution entirely (and with it, its performance gains). On my Haswell CPU, the perform
73.
by Ragib_Zaman 8y ago
I don't understand the "Though" part of this. The only reason any compiled language may be faster than another is because a compiler knows/assumes more about the code (either through users specification, or restrictions
74.
by Ragib_Zaman 8y ago
I'm currently getting a Masters in CS (specialising in ML) after leaving a pure math PhD. I'd love a research type job from anywhere, let alone Amazon, but every job posting for roles with 'research' in the title says th
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by Ragib_Zaman 8y ago
Their website seems to imply different: https://pytorch.org/get-started/locally/ E.g "To install PyTorch via Anaconda, and you are using CUDA 9.0, use the following conda command". If they are shipping w
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by Ragib_Zaman 8y ago
Its been considered ML ever since experts started writing books about ML (and before that, "pattern recognition"). Most introductory ML books cover it in some detail.
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by Ragib_Zaman 8y ago
Good point. The precision loss will be pretty bad if the numbers added above have greatly different magnitudes, which could occur if the next number (x) is very different to the current mean (mu), or if the list is very long. The first issu
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by Ragib_Zaman 8y ago
An 'online' mean calculation might resolve some of the common issues. Something like - def mean(ls): mu = 0.0 for i, x in enumerate(ls): mu = i/(i+1) * mu + x/(i+1) return mu
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by Ragib_Zaman 8y ago
Or the list is just very long.
80.
by Ragib_Zaman 8y ago
I think OP was saying he would be suspicious of a coder who was not interested in at least one area outside their professional domain, not any given area. If that's the case then I have to say I agree with them.
81.
by Ragib_Zaman 8y ago
This document is amazing. I'm interested in working in quant trading when I graduate, and I can't believe I haven't found this before. Do you think if I wrote my own back tester and test strategy and put it onto GitHub it wou
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by Ragib_Zaman 8y ago
> All blockers except uBlock Origin are available as JavaScript libraries which can be loaded in Node.js I may be incorrect, but I think their testing methodology involved loading a JavaScript version of the Brave adblocker and ran bench
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by Ragib_Zaman 8y ago
I'm sure this would be clarified in the book, but it seems their tips are best for gaining proficiency in quickly and accurately recollecting things you have already seen before, and not necessarily for learning something for the first
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by Ragib_Zaman 8y ago
YMMV indeed. Most devs aren't working with large C++ codebases with slow compile times and making $400k working only 40 weeks a year.
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by Ragib_Zaman 8y ago
> Do we possess a Bayesian brain that estimates probabilities in real time? You should read Daniel Kahneman's "Thinking Fast and Slow" - the answer is a resounding "No".
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by Ragib_Zaman 8y ago
Very much agreed. See my comment in this thread. The value of being able to build decent ML models is decreasing rapidly, so the difference maker will be acquiring better/more data (which you often have little control over) or better f
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by Ragib_Zaman 8y ago
I have a background in mathematics and am currently studying Machine Learning in a Master's program. Soon after I started I came to the same conclusion as the author of the article. It is becoming very easy for someone with some basic
88.
by Ragib_Zaman 8y ago
That is indeed how the subject has been developed historically and often introduced in optimisation courses. First one studies Linear Programs (minimize a linear function with affine equality and affine inequality constraints), then Quadrat
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by Ragib_Zaman 8y ago
Lagrange multipliers can be applied to solve optimization problems with equality constraints. KKT generalizes Lagrange multipliers to allow inequality constraints as well.