[Scilab-Dev] Machine Learning Toolbox

Wed May 31 16:41:38 CEST 2017

Hi,

I have received it, I'm planning to answer all those questions untill the
end of the week. Sorry for the delay.

On Wed, May 31, 2017 at 11:25 AM, Philippe Saade <
Philippe.Saade at esi-group.com> wrote:

> Hi all
> It looks like you didn't receive my first email ?
>
> Envoyé de mon mobile
>
> Le 31 mai 2017 à 16:20, Amanda Osvaldo <lambdasoftware at yahoo.es> a écrit :
>
>
> I everyone, I think we have nothing about it. <face-surprise.png>
> So ... somebody have a plan ? <face-surprise.png>
>
> -- Amanda Osvaldo
>
>
> On Mon, 2017-05-29 at 00:04 +0200, Philippe Saadé (ESI INENDI) wrote:
>
> Dear All,
>
> I took some time to jump in the discussion due to the fact that I wanted
> to get a better understanding of the current status of your discussions, a
> better understanding of Mandar's profile and expertise, and also what is
> easy/hard to do with Scilab to meet some serious and legitimate demands
> from Scilab's users.
>
> As I am the last to join the discussion, I will voluntarily reset my mind
> and start again the discussions with you so that we can try to structure
> the project and converge quickly on an achievable list of goals for this
> GSoC.
>
> For that purpose, I would like to list a series of questions on which we
> need to share a mutual list of answers and common understanding.
> This should serve as a basis to decide what to do, how and when.
>
> So, feel free to fill in...
>
>
>    1. Scilab has a way to use Python : PIMS. Originaly created in August
>    2014.
>       1. How mature do you think it is?
>       2. How compatible is it with the potential need of using existing
>       Python-based ML framework from within Scilab?
>       3. How easy/hard would it be for Mandar to pursue what has been
>       done here so that using the ML frameworks from Scilab would be working
>       well?
>    2. Data Management. I think the questions related to the actual size
>    of the data that would be possibly handled by Scilab's users is key. Many
>    ML methods (not necessarily "Deep" ones) need to be trained on large data
>    sets. It doesn't mean that everything has to sit in RAM during training or
>    general pre-processing but it must be possible to handle large data sets.
>       1. Do we use only "pointers" from Scilab to give an access to the
>       real data structures that are used by the ML frameworks?
>       2. Do we want to integrate part or all of the data structures that
>       are useful, as native Scilab data structures?
>       3. Do we consider that the execution of ML algorithms should be
>       designed and architectured in a way that it is done "remotely" from the
>       perspective of Scilab?
>       3. Use Cases. We need to list some use cases that are typical of
>    what Scilab users do and that make the usage of ML an exciting perspective.
>    If we can not demonstrate that ML within Scilab is possible, easy and
>    really useful on these Use cases, I am not sure we will have reached the
>    main target of that GSoC opportunity.
>    Can we list use cases together?
>    I will start by items some but your input is important here.
>       1. image classification
>       2. object recognition in images and video
>       3. Data Driven Industrial Process Control
>       4. Anomaly Detection
>       5. Dimensionality / Model reduction
>       6. etc.
>
>
> For sure, these questions do not cover all the important topics for this
> "ML Toolbox" project but this is a way to bootstrap.
> As we know, we need to be active and efficient for the 30th of May!
>
> Thanks for your feedback and feel free to share your point of view.
>
>
>
>
> Cordialement – Best regards,
>
>
>
> Philippe SAADÉ
> * <http://www.esi-group.com/>*
>
>
> Le 18/05/2017 à 21:50, Amanda Osvaldo a écrit :
>
> Hi everybody, can I made some questions ?
>
> First, at all, I really agree that SciLab needs a Machine Learning toolbox.
>
> However, I'm pretty critical about Scilab in your limitations.
> *I see very potential in the software but require a reform in your
> infrastructure.*
>
>
> So, my questions.
>
> How large are we talking about the training dataset in scilab ?
> Even with Tensorflow compatibility if you need to put all the dataset into
> the RAM I fear the toolbox utility will be very limited.
> In another words: The toolbox will can handle a 250GB dataset or just a
> few GBs from a desktop ?
>
> Have I read right ?
> We are talking about to integrate Scilab and tensorflow or scikit-learn ?
> I think it's a good idea, I just whant to know if I'm interpreting right.
>
> Somebody have some idea how to handle this project in a software
> engineering perspective?
> Just to ensure the tests and code quality.
>
>
> -- Amanda Osvaldo
>
>
> On Thu, 2017-05-18 at 16:01 +0000, Yann Debray wrote:
>
> Dear Caio, Dhruv and Amanda,
>
>
>
> I would like to include my colleague Philippe Saadé to the exchanges on
> Machine Learning for Scilab.
>
> He is an experienced mathematician working with us at ESI Group, and has
> an interesting vision on the subject.
>
> He will be scientific advisor and mentor for a joint internship on Machine
> learning starting mid june.
>
>
>
> @Philippe Saadé   (ESI INENDI) <philippe.saade at esi-group.com>: Could you
> maybe share with us your view on the subject?
>
>
>
> We can keep this exchange public if it is alright with you all, since I
> believe our success on the subject will depend on our capacity to
> centralize and merge our community efforts.
>
> You can all collaborate on the project on our forge:
>
> http://forge.scilab.org/index.php/p/machine-learning-toolbox/
>
>
>
> Yours
>
> Yann @ Scilab
>
>
>
> *De : *Amanda Osvaldo <lambdasoftware at yahoo.es> <lambdasoftware at yahoo.es>
> *Date : *vendredi 28 avril 2017 à 01:03
> *À : *List dedicated to the development of Scilab <dev at lists.scilab.org>
> <dev at lists.scilab.org>, Yann Debray <Yann.Debray at esi-group.com>
> <Yann.Debray at esi-group.com>, Dhruv Khattar <dhruvk1996 at gmail.com>
> <dhruvk1996 at gmail.com>
> *Objet : *Re: [Scilab-Dev] Machine Learning Toolbox
>
>
>
> Hi Caio, sorry for the late.
>
>
>
> *I think we should ask ourselves what SciLAB's focus and what audience
> are.*
>
> *I feel a lack of knowing what users of Scilab seek.*
>
>
>
> Me, for example, I want to do everything from protyping to running the
> script on hundreds of Intel Xeon servers with the least possible effort.
>
> Even with less effort than it would have if the script were built in
> Python.
>
>
>
> I am sure that new data structures will expand the use of SciLAB.
>
>
>
> But what advantage will this bring to users?
>
> Python, as example, have already optimized data structures and libraries.
>
>
>
> -- Amanda Osvaldo
>
>
>
>
>
> On Wed, 2017-04-26 at 14:32 -0300, Caio Souza wrote:
>
> Hi,
>
>
>
>
>
> I have been thinking about the usability of the toolbox and independent of
> which algorithms we are going to have, would be interesting to have some
> simplified structure (like TensorFlow).
>
>
>
> Despite it being a lot of work to have such structure, (data, model, cost
> function, minimizer), it would make the toolbox easy to use and extend,
> having minimum impact to the usability.
>
>
>
> IMHO, this is something that should be defined before any coding starts,
> and also well explained to the student.
>
>
>
> I would like to hear from you what do you think, so we can start a
> discussion.
>
>
>
>
>
> Best,
>
> Caio SOUZA
>
> _______________________________________________
>
> dev mailing list
>
> dev at lists.scilab.org
>
> http://lists.scilab.org/mailman/listinfo/dev
>
>
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <https://lists.scilab.org/pipermail/dev/attachments/20170531/30271d87/attachment.htm>