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

[Abhinav Gupta]

Hi Marcus,
   I'hv also created a wiki page on github.

https://github.com/abhinvgpta/mlpack/wiki/Example-of-Feed-Forward-Network-using-mlpack
   Please have a look.

Thanks,
Abhinav

On Mon, Apr 18, 2016 at 1:16 PM, Abhinav Gupta <abhinavgupta440 at gmail.com>
wrote:

> Hi Marcus,
>    I'hv preprocessed the Internet Advertisements dataset and implemented
> the example using FFN. I'hv created and shared a google doc with you where
> I'm adding some background information about the dataset and the method
> used.
>
> I used the test case example.
> If you get time can you please check my approach and let me know if I'm
> going in the wrong direction.
>
> Thanks,
> Abhinav
>
> On Sat, Apr 16, 2016 at 2:52 AM, Abhinav Gupta <abhinavgupta440 at gmail.com>
> wrote:
>
>> Hi Marcus,
>>   So I'll get started with the Internet Advertisements dataset and
>> implement FFN for it, followed by Convolututional Network for it and FFN
>> for Human Activity Recognition Using Smartphones dataset. I'm sharing a doc
>> with you where I'll get started with the implementation of the first task
>> (implementing FFN for Internet Advertisements dataset).
>>
>> As I'm new to the process please let me know if you feel that I should
>> change my methodology at some points.
>>
>> Thanks,
>> Abhinav
>>
>> On Thu, Apr 14, 2016 at 11:11 PM, Marcus Edel <marcus.edel at fu-berlin.de>
>> wrote:
>>
>>> Hello Abhinav,
>>>
>>> nice to hear from you. You found some really interesting dataset and
>>> except for
>>> the "Anonymous Microsoft Web Data Data Set" which is a categorical
>>> dataset, we
>>> can definitely use the datasets for some neat examples. I like that none
>>> of the
>>> datasets looks like the other. So we could show e.g that a convolution
>>> neural
>>> network is the preferred model for the Internet Advertisements Data Set
>>> as like
>>> maybe a standard feed-forward network. I guess, we should start with one
>>> of the
>>> datasets first and see how things go, what do you think?
>>>
>>> Thanks again, for taking the time to look into this.
>>>
>>> Thanks,
>>> Marcus
>>>
>>> On 14 Apr 2016, at 00:58, Abhinav Gupta <abhinavgupta440 at gmail.com>
>>> wrote:
>>>
>>> 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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