[Openchemistry-developers] Interested in Machine learning applied to parsing computational chemistry output

[Karol Langner]

Hi Yue,

CC'ing relevant mailing lists.

Nice to hear from you. To get started, I would recommend taking a look
around the cclib repository (https://github.com/cclib/cclib) and docs (
https://cclib.github.io/how_to_parse.html). The docs are not perfect, but
give a reasonable overview (of course, please tell us what to improve). If
you feel like digging into some contributions, feel free to send a pull
request on GitHub or to peruse our current list of bugs and issues (
https://github.com/cclib/cclib/issues).

As far as the ML project is concerned, it would somewhat more research-y
than the other projects, simply because we haven't really tried to do this
before. We would expect a student to independently survey what approaches
would be reasonable, and define the metrics/assumption that can be applied.

Hope that helps somewhat, don't hesitate to ask more questions.

- Karol


On Sat, Feb 24, 2018 at 4:48 AM, Yue Wang <ywang337 at jhu.edu> wrote:

> Hi Karol,
>
>
> I am a student at Johns Hopkins University and I am interested in your
> project idea: Machine learning applied to parsing computational chemistry
> output.
>
> I've experience with Python and Machine Learning and participated in
> Kaggle competition and UW's Data Science Incubator program. Also, I
> worked with Prof. Xiao Gu during my undergrad to do DFT calculation and
> participated in a project exploring alkali-resistant mechanism of a
> Hollandite deNOx catalyst, which was published on Environ. Sci. Technol in
> 2015.
>
> But I'm new to open source project and I do not know how to work with cclib
> to make some contribution. Could you give me some guide?
>
> Thanks!
>
> Best,
> Yue
>
>
>
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