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 < [email protected]> 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 <[email protected]> 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) <[email protected]>: 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 <[email protected]> <[email protected]> > *Date : *vendredi 28 avril 2017 à 01:03 > *À : *List dedicated to the development of Scilab <[email protected]> > <[email protected]>, Yann Debray <[email protected]> > <[email protected]>, Dhruv Khattar <[email protected]> > <[email protected]> > *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 > > [email protected] > > http://lists.scilab.org/mailman/listinfo/dev > > >
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