[Air-L] Data Science Intensive Training for Ph.D.s
Hamlet López García
hamlet.lopez at cubarte.cult.cu
Fri Feb 24 16:10:55 PST 2017
Thanks Elijah! The Quanteda package looks very promising!
El 24/02/2017 a las 9:04, Elijah Wright escribió:
>
> Because I was playing with it quite a bit recently... check out the
> quanteda package in R. It's got a bunch of very convenient methods
> pulled together in one place - things we would have had to think a lot
> harder about, or pull in from other packages (porter stemmer, etc) a
> decade ago.
>
> (If you're reading ML texts you're probably running across more quant
> methods than qualitative.... hopefully this gives you a few ways to
> shortcut your analysis and spend more time on thinking and less on
> drudge-programming... )
>
> --e
>
>
> On Wed, Feb 22, 2017 at 7:41 PM, Hamlet López García
> <hamlet.lopez at cubarte.cult.cu <mailto:hamlet.lopez at cubarte.cult.cu>>
> wrote:
>
> Dear colleagues,
>
> I also think a repo/forum/listserve would be a really great idea.
> I know a little of programing, mainly in Java, and right now I am
> struggling with a corpus of around 4000 emails of a free software
> community, for my PhD in Social Communication. So it will be great
> to share references and suggestions. So far I am studying with the
> book Machine Learning in Action, by Peter Harrington (Manning,
> 2012), a very accessible text. Also I am exploring the possibility
> of a classifier based on Apache Lucene, to facilitate the
> qualitative categorization of emails.
>
> Best
>
> Hamlet
>
>
>
>
> El 22/02/2017 a las 12:46, Matthew T Mccarthy escribió:
>
> Hi All,
> I’ve also been exploring data science in my off time. I
> started learning the basics of ML algos with a Udemy course,
> but have been supplementing that very general instruction with
> O’Reilly texts on data science using R, SQL, and others. I
> think a repo/forum/listserv would be a really great idea.
>
> For information Kaggle.com<http://Kaggle.com> has been helpful.
> For open data data.world also seems to be a good source.
>
> Best,
> Matt
>
> Matthew T. Mccarthy
> Ph.D. Candidate/Lecturer
> PO Box: 413 Milwaukee, WI 53201
> University of Wisconsin - Milwaukee
>
>
>
>
>
> On Feb 22, 2017, at 2:10 PM, Lauri Goldkind
> <goldkind at fordham.edu
> <mailto:goldkind at fordham.edu><mailto:goldkind at fordham.edu
> <mailto:goldkind at fordham.edu>>> wrote:
>
> Hi Craig,
>
> I am a CS DBMS dropout. I must admit I found the teaching
> style daunting as
> a returning student (memorize SQL code cold).
>
> The shared repository would be very welcome.
>
> Best,
> Lauri.
>
> _________________________________________
> Lauri Goldkind, PhD
> Graduate School of Social Service
> Fordham
> http://www.laurigoldkind.net/
>
> There is nothing in a caterpillar that tells you its going to
> be a butterfly.
>
> --- Buckminster Fuller (1895-1983)
>
>
> On Wed, Feb 22, 2017 at 3:10 AM, Craig Hamilton
> <Craig.Hamilton at bcu.ac.uk <mailto:Craig.Hamilton at bcu.ac.uk>>
> wrote:
>
> Dear Jose,
>
>
>
> I’d be happy to share some of my experiences with you. From a
> standing
> start about 18 months ago, during my own PhD, I took a similar
> decision.
> During that time I’ve managed to learn some basic programming
> and have been
> able to use some data science techniques on my own data. Drop
> me a line if
> you’d like to discuss things. To start with, I’d recommend the
> Partially
> Derivative podcast. This is a magazine show about data, data
> science and so
> on, that will give you a good feel for the field as an
> outsider. I found
> this episode from a couple of years ago particularly good as a
> ‘Where to
> start’ guide:
> https://urldefense.proofpoint.com/v2/url?u=http-3A__
> <https://urldefense.proofpoint.com/v2/url?u=http-3A__>
> partiallyderivative.com_news_2015_01_09_episode-2D9-2Dthe-
> 2Done-2Dthat-2Dwill-2Dtotally-2Dchange-2Dyour-2Dlife&d=DwIGaQ&c=
> aqMfXOEvEJQh2iQMCb7Wy8l0sPnURkcqADc2guUW8IM&r=
> Zm5R0WfUGSV1wBpvGCnQPiijPYegJoKsm7pYy73Uvps&m=AmPT-
> BHXMJ387Lx8h5M5vPidprcokhRADNDIwbLVzXo&s=PqpfcFwEmLgmEZ_
> appqqS20zqGsmnP2HUo3_Y9sdgqE&e= .
>
>
>
> If any other AoIR list colleagues think it would be useful to
> set up some
> sort of group discussion/repository of resources for social
> science/humanities scholars, I’d be happy to be involved.
>
>
>
> Kind regards
>
> Craig
>
>
>
> On 22 Feb 2017, at 05:19, Jose Marichal <jfmarichal at gmail.com
> <mailto:jfmarichal at gmail.com><mailto:j <mailto:j>
> fmarichal at gmail.com <mailto:fmarichal at gmail.com>>> wrote:
>
>
>
> Colleagues,
>
>
>
> I'm a mid-career Ph.D. social scientist going on sabbatical
> next year and
>
> I'd like to immerse myself in learning different aspects of data
>
> science/machine learning... I'd be grateful if folks could
> recommend
>
> programs or opportunities for Ph.D.'s to learn these tools.
>
>
>
> Warm regards,
>
> Jose Marichal
>
> California Lutheran University
>
>
>
> --
>
> ____________________________________________________________
> ___________________________
>
>
>
> josé marichal, ph.d. | professor and chair| political science
> department |
>
> california lutheran university
>
> 60 w. olsen road | #3800 | thousand oaks, ca 91360
>
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> --
> MsC. Hamlet López García
> Investigador Auxiliar ICIC Juan Marinello
> doctorando por la Facultad de Comunicación, Universidad de la Habana
>
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--
MsC. Hamlet López García
Investigador Auxiliar ICIC Juan Marinello
doctorando por la Facultad de Comunicación, Universidad de la Habana
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