[mlpack] Interested in writing documentation for Mlpack's ann module

[Abhinav Gupta]

Hi Marcus,
  Sorry for the late response.
I'hv shortlisted these datasets, please have a look at them.

http://archive.ics.uci.edu/ml/datasets/Internet+Advertisements

http://archive.ics.uci.edu/ml/datasets/Human+Activity+Recognition+Using+Smartphones

http://archive.ics.uci.edu/ml/datasets/Anonymous+Microsoft+Web+Data

http://archive.ics.uci.edu/ml/datasets/Tic-Tac-Toe+Endgame

Please let me know if you find any one of them appropriate to mention in
the example or if you have some comments regarding the datasets. In the
meanwhile I'll be looking for more.

Thanks,
Abhinav

On Mon, Apr 11, 2016 at 6:11 AM, Marcus Edel <marcus.edel at fu-berlin.de>
wrote:

> Hello Abhinav,
>
> sounds great to me. The UCI repository is probably a good start:
> https://archive.ics.uci.edu/ml/datasets.html Also sharing a doc so that
> we can
> work together on it is a good idea. I look forward to hearing from you.
>
> Thanks,
> Marcus
>
> On 10 Apr 2016, at 10:01, Abhinav Gupta <abhinavgupta440 at gmail.com> wrote:
>
> Hi Marcus,
>     So I'll look for some datasets, make a list and will share them with
> you. Once we settle on the dataset I'll share a doc with the information
> about model, dataset and the example like you mentioned. And I think
> representing dataset with few neat images can be taken care of while
> choosing the dataset.
>
> Please let me know if it sounds good to you.
>
> Thanks,
> Abhinav
>
> On Sat, Apr 9, 2016 at 4:58 AM, Marcus Edel <marcus.edel at fu-berlin.de>
> wrote:
>
>> Hello Abhinav,
>>
>> I think it would be a good idea, to include some examples and to explain
>> the
>> examples step by step; probably with some sort of background information
>> about
>> the model and the dataset used. Maybe we can come up with some neat
>> images, for
>> the dataset. If you like, you can start with that, don't feel obligated
>> to do
>> so. Also, if you don't like the idea, that's also fine, in this case, we
>> can
>> come up with other ideas.
>>
>> Also, I'm not sure we should use the thyroid dataset for the examples,
>> it's kind
>> of an uninteresting dataset, don't you think? Don't get me wrong, the
>> dataset is
>> great and important, but maybe we can find something fancy.
>>
>> Thanks,
>> Marcus
>>
>> On 07 Apr 2016, at 08:09, Abhinav Gupta <abhinavgupta440 at gmail.com>
>> wrote:
>>
>> Hii Marcus,
>>    Sure I would love to collaborate with you. I'hv started going through
>> amf's documentation.
>>
>> I'hv successfully run the test cases as independent examples like I
>> mentioned in the issue: https://github.com/mlpack/mlpack/issues/562 If
>> you like we can include those, or come up with more different examples.
>>
>> Please let me know the procedure you would like me to follow, to
>> collaborate in an efficient manner.
>>
>> Thanks,
>> Abhinav
>>
>>
>> On Wed, Apr 6, 2016 at 3:57 AM, Marcus Edel <marcus.edel at fu-berlin.de>
>> wrote:
>>
>>> Hello Abhinav,
>>>
>>> sorry for the slow response. We think that the best documentation is
>>> written by
>>> the person who wrote the code. That doesn't mean, we don't appreciate
>>> any help
>>> with the documentation. I guess the person who wrote the code, has a
>>> different
>>> view on what might be helpful and what is trivial as another user. So,
>>> if you
>>> like we can combine both views and write a strong documentation, what do
>>> you
>>> think?
>>>
>>> The documentation should be based on the already existing tutorials, you
>>> could
>>> take a look at the amf tutorial. I think, it would be nice to include
>>> some neat
>>> examples.
>>>
>>> Thanks,
>>> Marcus
>>>
>>> > On 03 Apr 2016, at 09:11, Abhinav Gupta <abhinavgupta440 at gmail.com>
>>> wrote:
>>> >
>>> > Hi Ryan, Marcus ,
>>> >      I'm interested in writing a basic documentation on how to use
>>> mlpack to build neural networks along with few basic examples (derived
>>> mostly from the test cases). If someone is already working on this I would
>>> love to collaborate with him/her.
>>> > Also is there any standard procedure that you would like me to follow ?
>>> >
>>> > Thanks,
>>> > Abhinav
>>>
>>>
>>
>>
>
>
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