Re: [cclib-devel] Regarding machine learning to complement cclib

[Karol L. <kar...@gm...>]

Hi Aditya,

My intention with the idea was solely data extraction from log files, so
parsing. But if you see other applications of ML within the scope of cclib,
we're definitely interested. Please note other projects under the
OpenChemistry umbrella also have ML ideas, and many of those are more
straightforward. Here, with parsing, things will be much more researchy.


HTH,
Karol

On Tue, Jan 29, 2019, 2:13 AM Aditya Kamath <adt...@gm...> wrote:

> Dear Karol,
> I am Aditya, I read your GSoC project Idea to possibly implement machine
> learning to compete with cclib as an efficient data parser. From what I
> understand, you wish to train a machine learning model to handle and
> convert data between various software outputs.
>
> I suggest that the role of machine learning is not to handle or parse data
> but rather to analyze it. cclib can benefit from backend trained ML models
> to do tasks like classify file data, identify and extract information from
> files. It can also perform very accurate regression and emulate complex
> function maps which could benefit any calculation methods used by cclib.
>
> We can use algorithms like CRF's to label and identify data in data files
> or use neural networks or any other regression methods to compliment
> calculations.
>
> I am a final year student, looking for a prospective GSoC project to work
> with. I have previously worked with a research group implementing machine
> learning for ODE solvers to compete with Gaussian software calculations, ab
> initio calculations. I would be happy to discuss further on how we can work
> with cclib functionalities. I look forward to hearing from you.
>
> Best Wishes,
> Aditya Kamath
>