#mlpack on 2019-12-29 — irc logs at libera.irclog.whitequark.org

2018-11-12 22:39 ChanServ changed the topic of #mlpack to: "mlpack: a fast, flexible machine learning library :: We don't always respond instantly, but we will respond; please be patient :: Logs at http://www.mlpack.org/irc/

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02:44 < rcurtin> zoq: yeah, ensmallen is a little weak on the other stuff though :-D

02:47 < abernauer[m]> rcurtin: Any thoughts on this Algortihms book? I am thinking about getting a copy. https://www.amazon.com/Algorithm-Design-Manual-Steven-Skiena/dp/1849967202?pf_rd_p=dd4f5b57-ba5b-418b-a348-64ec62df14cc&pd_rd_wg=WdzTm&pf_rd_r=M155MF6WP3WD1AYPYW61&ref_=pd_gw_cr_simh&pd_rd_w=rTezD&pd_rd_r=6a9615b8-8476-40fc-acd7-a8e716f6a48a

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02:51 < rcurtin> abernauer[m]: not sure, not familiar with it unfortunately

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03:01 < abernauer[m]> It's not a theoretical text and has C pseudocode.

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04:08 < RohitKartikGitte> @rcurtin that's a great book, have you ever read [Introduction to Algorithms](https://www.amazon.com/Introduction-Algorithms-Leiserson-published-Hardcover-dp-B008F1DKXU/dp/B008F1DKXU/ref=mt_paperback?_encoding=UTF8&me=&qid=1577592332)

04:08 < RohitKartikGitte> both these books are really great.

04:11 < rcurtin> I'm definitely familiar with the CLRS algorithms book, and that one is definitely good :)

04:11 < rcurtin> sounds like I should add The Algorithm Design manual to my list

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04:16 < RohitKartikGitte> cool :)

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04:26 < RohitKartikGitte> which sem are you currently in rcutin?

04:26 < RohitKartikGitte> (edited) ... in rcutin? => ... in rcurtin?

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05:22 < rcurtin> I defended my PhD four years ago, so not currently a part of any semester :)

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08:15 < jenkins-mlpack2> Project docker mlpack nightly build build #567: NOW UNSTABLE in 3 hr 1 min: http://ci.mlpack.org/job/docker%20mlpack%20nightly%20build/567/

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08:22 < ShikharJaiswalGi> @aberbauer Steven Skiena is a very skilled problem designer and problem solver as well. If interview prep is your goal, there isn't a better text available than this. Some people suggest Cracking The Coding Interview by Gayle Laakmann McDowell, but that is too easy in my opinion (the last section on hard problems is good though).

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17:03 < RohitKartikGitte> nice @rcurtin

17:06 < RohitKartikGitte> @ShikharJ that's great advice. would Cracking the Coding Interview be of help in case of FANG?

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18:25 < ShikharJaiswalGi> @OO7kartik AFAIK Netflix doesn't hire people straight out of schools. Amazon's process is by far the easiest out of the four, you probably wouldn't even need CTCI. I have given Google's snapshot coding sample (which is the standard interview qualifier for North America) and the questions were simply chapter exercise level problems. I have no experience of interviewing with Facebook, but I have a number of friends who

18:25 < ShikharJaiswalGi> did, and they don't think of the process being wildly different from Google. Hope this helps.

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19:06 < Nakul[m]> https://github.com/mlpack/mlpack/wiki/SummerOfCodeIdeas#essential-deep-learning-modules

19:06 < Nakul[m]> i noticed here ```Automatic bindings to new languages``` the link http://www.mlpack.org/docs/mlpack-git/doxygen/bindings.html is broken

19:06 < Nakul[m]> it would be nice to update

19:08 < zoq> Nakul[m]: We will update the ideas pages in the next days/weeks.

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