Hi Lakini, You can gain some insight for your NN builder from TensorFlow Playground [1]. It is also open source under Apache 2.0 licence [2].
[1] http://playground.tensorflow.org [2] https://github.com/tensorflow/playground Regards, CD On Thu, Jun 2, 2016 at 8:00 AM, Upul Bandara <u...@wso2.com> wrote: > Yes at the moment this looks OK. > > Please put some effort to create a basic version of the NN builder and > let's have a quick demo. > > Let me know if you have further questions or clarifications. > > Thanks, > Upul > > On Wed, Jun 1, 2016 at 11:29 PM, Lakini Senanayaka < > lakinisenanayak...@gmail.com> wrote: > >> Hi, >> >> Thank you very much Upul. I will submit a demo soon. >> >> I have drawn a sketch of NN builder front end[1]. Basically it will be >> like this UI[2].(The content will be changed.) >> >> [1]Sketch of NN Builder >> <https://docs.google.com/document/d/1c9F5xECaxuXq65RJaBO33AZZqMN0qNJsqeux3tRfUHE/edit?usp=sharing> >> [2]https://www.draw.io/ <https://www.draw.io/> >> >> In [1],under "layers" users can select the type of the layer-Input,Hidden >> or Output layer. >> Under "node" and "Connectors"-users can drag and drop nodes and >> connectors to the working area and they can build their NN as they wish. >> >> In the right hand side,there is a setting area.From that user can set >> Optimization algorithms,iterations,learning rates,seed etc. of the neural >> network. >> >> Could you please give me comments and your thoughts regrading this? >> >> Thank you. >> >> >> >> On Wed, Jun 1, 2016 at 2:19 PM, Upul Bandara <u...@wso2.com> wrote: >> >>> Hi, >>> >>> Good progress. >>> >>> The key parts of the project are designing the front-end of NN builder, >>> communicating between the front-end and the Deeplearning4J back-end. >>> So at this stage of the project, it is better to put your effort on >>> above the components. Later, we can integrate what you have built with WSO2 >>> Machine Learning server. >>> >>> Once you have completed a basic NN builder (ability to build a simple >>> feedforward is enough) we would like to have a quick demo. >>> >>> Let me know if you have further questions or clarifications. >>> >>> Thanks, >>> Upul >>> >>> On Wed, Jun 1, 2016 at 10:42 AM, Lakini Senanayaka < >>> lakinisenanayak...@gmail.com> wrote: >>> >>>> Hi, >>>> >>>> I'm sorry for the late response.Thank you very much for the last >>>> email.I have gone through JQueryUI and I have implemented some samples >>>> using JQueryUI.I have gone through the WSO2 machine learner and I have >>>> identified the place to insert this jaggery page(replace the >>>> hyper-parameter page in the ML UI). >>>> Currently I'm designing the sketch of the Deep Neural Network >>>> Builder-the front end. >>>> I'll send my sketch before tonight.Based on your comments I can start >>>> implementations. >>>> >>>> Thank you. >>>> >>>> >>>> On Wed, Jun 1, 2016 at 9:29 AM, Supun Sethunga <sup...@wso2.com> wrote: >>>> >>>>> Hi Lakini, >>>>> >>>>> Any update on the progress? >>>>> >>>>> Regards, >>>>> Supun >>>>> >>>>> On Fri, May 27, 2016 at 5:34 PM, Supun Sethunga <sup...@wso2.com> >>>>> wrote: >>>>> >>>>>> Hi Lakini, >>>>>> >>>>>> Sorry for the delayed response. As the first part of the project, you >>>>>> can start the work on the UI/drag and drop feature, as the core of your >>>>>> project is based around that. Therefore, shall we try to get a basic >>>>>> version of drag and drop UI, by the mid-term evaluation? (No need to >>>>>> connect the UI with the dl4j, for the first phase) So this would be >>>>>> include: >>>>>> >>>>>> - A link/re-direct to go to Visual builder, upon selecting the >>>>>> Neural Netowrks (as the algorithm) >>>>>> - The drawing/dropping area and a panel to pick the objects to be >>>>>> dragged (objects as in, nodes, layers, links, etc) >>>>>> >>>>>> This drag and drop page should replace the hyper-parameter page in >>>>>> the ML UI. More precisely, In the Machine Learner wizard, when a user >>>>>> picks >>>>>> the algorithm name as Neural Network, and proceed, this drag and drop >>>>>> page >>>>>> should be prompted instead of the hyper-parameters page. You can create >>>>>> the >>>>>> overall page as a jaggery page (.jag). It would be easier for you to get >>>>>> a >>>>>> copy of an existing page, and modifying the content. That will preserve >>>>>> the >>>>>> existing styles, session handling etc. >>>>>> >>>>>> Please feel free to raise any question you come across during >>>>>> implementing. >>>>>> >>>>>> Regards, >>>>>> Supun >>>>>> >>>>>> On Tue, May 24, 2016 at 8:09 PM, Lakini Senanayaka < >>>>>> lakinisenanayak...@gmail.com> wrote: >>>>>> >>>>>>> Hi, >>>>>>> >>>>>>> Thank you very much for the suggestions.I will be using JQueryUI. >>>>>>> >>>>>>> As my coding period started yesterday according to the GSoC Schedule >>>>>>> I would like to know the workload that should be completed >>>>>>> before the midterm evaluation. Please advise me accordingly. >>>>>>> >>>>>>> Thank you. >>>>>>> >>>>>>> >>>>>>> On Tue, May 24, 2016 at 10:34 AM, Supun Sethunga <sup...@wso2.com> >>>>>>> wrote: >>>>>>> >>>>>>>> Hi Lakini, >>>>>>>> >>>>>>>> Yes you can use any of them, with open source licence. But I would >>>>>>>> prefer JQueryUI, as its a well known library, and is already been used >>>>>>>> by >>>>>>>> some of the wso2 products. >>>>>>>> >>>>>>>> Regards, >>>>>>>> Supun >>>>>>>> >>>>>>>> On Tue, May 24, 2016 at 9:29 AM, Lakini Senanayaka < >>>>>>>> lakinisenanayak...@gmail.com> wrote: >>>>>>>> >>>>>>>>> Hi, >>>>>>>>> >>>>>>>>> I have found some libraries to build drag and drop UI for our >>>>>>>>> front end .They are JQury UI[1],Dragula[2],Draggablily[3]. >>>>>>>>> I hope I can do the developments using these libraries. >>>>>>>>> >>>>>>>>> [1]jqueryui <http://jqueryui.com/> >>>>>>>>> [2]dragula <https://bevacqua.github.io/dragula/> >>>>>>>>> [3]draggabilly <http://draggabilly.desandro.com/> >>>>>>>>> >>>>>>>>> Could you please tell me if you have any other suggestions? >>>>>>>>> >>>>>>>>> On Sat, May 21, 2016 at 11:05 PM, Lakini Senanayaka < >>>>>>>>> lakinisenanayak...@gmail.com> wrote: >>>>>>>>> >>>>>>>>>> Hi , >>>>>>>>>> >>>>>>>>>> This is my weekly progress update of my project. >>>>>>>>>> >>>>>>>>>> I have solved all the problems I have mentioned in the last >>>>>>>>>> email.I could find a class BaseDatasetIterator which is in DL4J >>>>>>>>>> where we >>>>>>>>>> can find inbuilt iterators for CurvesDataSetIterator, >>>>>>>>>> IrisDataSetIterator, MnistDataSetIterator, >>>>>>>>>> MovingWindowBaseDataSetIterator, RawMnistDataSetIterator .There >>>>>>>>>> is no iterator for CIFAR dataset yet. >>>>>>>>>> >>>>>>>>>> I have gone through the whole documentation except Deeplearning4j >>>>>>>>>> on Spark.The latest documentation is very understandable than the >>>>>>>>>> earlier >>>>>>>>>> one.I have studied neural networks- Restricted Boltzmann >>>>>>>>>> Machines, >>>>>>>>>> Convolutional Nets (ConvNets), >>>>>>>>>> Long Short-Term Memory Units (LSTMs), >>>>>>>>>> Denoising Autoencoders, >>>>>>>>>> Recurrent Nets and LSTMs, >>>>>>>>>> Multilayer Neural Nets, >>>>>>>>>> Deep-Belief Network, >>>>>>>>>> Deep AutoEncoder, >>>>>>>>>> Stacked Denoising Autoencoders >>>>>>>>>> >>>>>>>>>> I have run the example codes[1] and I have understood the >>>>>>>>>> implementations.I have rerun the codes with modifying different >>>>>>>>>> parameter >>>>>>>>>> values like number and size of the hidden layers, learning rate, >>>>>>>>>> momentum, >>>>>>>>>> weight distribution and various types of regularization and checked >>>>>>>>>> the >>>>>>>>>> performance. >>>>>>>>>> >>>>>>>>>> I have implemented a convolution net[3] and trained it using LFW >>>>>>>>>> dataset[2] and a Recurrent net[4].Still I have a problem in >>>>>>>>>> vectorizing >>>>>>>>>> CIFRA-10 data set. >>>>>>>>>> >>>>>>>>>> Currently I am researching about libraries to build drag & >>>>>>>>>> drop UI for front end. >>>>>>>>>> >>>>>>>>>> [1]dl4j-0.4-examples >>>>>>>>>> <https://github.com/deeplearning4j/dl4j-0.4-examples> >>>>>>>>>> [2]LFW Face Dataset <http://vis-www.cs.umass.edu/lfw/> >>>>>>>>>> [3]ConvolutionNetLFW >>>>>>>>>> <https://github.com/Lakini/Deeplearning4Java/blob/master/src/main/java/org/deeplearning4j/examples/convolution/ConvolutionNetLFW.java> >>>>>>>>>> [4]RecurrentNetworkExample >>>>>>>>>> <https://github.com/Lakini/Deeplearning4Java/blob/master/src/main/java/org/deeplearning4j/examples/recurrent/basic/RecurrentNetworkExample.java> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> Could you please guide me to do the next step of my project . >>>>>>>>>> >>>>>>>>>> Thank you. >>>>>>>>>> >>>>>>>>>> Sincerely, >>>>>>>>>> *Lakini Senanayaka.* >>>>>>>>>> >>>>>>>>>> >>>>>>>>> >>>>>>>>> >>>>>>>>> -- >>>>>>>>> Thank you. >>>>>>>>> >>>>>>>>> Sincerely, >>>>>>>>> *Lakini Senanayaka.* >>>>>>>>> >>>>>>>>> >>>>>>>> >>>>>>>> >>>>>>>> -- >>>>>>>> *Supun Sethunga* >>>>>>>> Software Engineer >>>>>>>> WSO2, Inc. >>>>>>>> http://wso2.com/ >>>>>>>> lean | enterprise | middleware >>>>>>>> Mobile : +94 716546324 >>>>>>>> >>>>>>> >>>>>>> >>>>>>> >>>>>>> -- >>>>>>> Thank you. >>>>>>> >>>>>>> Sincerely, >>>>>>> *Lakini Senanayaka.* >>>>>>> >>>>>>> >>>>>> >>>>>> >>>>>> -- >>>>>> *Supun Sethunga* >>>>>> Software Engineer >>>>>> WSO2, Inc. >>>>>> http://wso2.com/ >>>>>> lean | enterprise | middleware >>>>>> Mobile : +94 716546324 >>>>>> >>>>> >>>>> >>>>> >>>>> -- >>>>> *Supun Sethunga* >>>>> Software Engineer >>>>> WSO2, Inc. >>>>> http://wso2.com/ >>>>> lean | enterprise | middleware >>>>> Mobile : +94 716546324 >>>>> >>>> >>>> >>>> >>>> -- >>>> Thank you. >>>> >>>> Sincerely, >>>> *Lakini Senanayaka.* >>>> >>>> >>> >>> >>> -- >>> Upul Bandara, >>> Associate Technical Lead, WSO2, Inc., >>> Mob: +94 715 468 345. >>> >> >> >> >> -- >> Thank you. >> >> Sincerely, >> *Lakini Senanayaka.* >> >> > > > -- > Upul Bandara, > Associate Technical Lead, WSO2, Inc., > Mob: +94 715 468 345. > > _______________________________________________ > Dev mailing list > Dev@wso2.org > http://wso2.org/cgi-bin/mailman/listinfo/dev > > -- *CD Athuraliya* Software Engineer WSO2, Inc. lean . enterprise . middleware Mobile: +94 716288847 <94716288847> LinkedIn <http://lk.linkedin.com/in/cdathuraliya> | Twitter <https://twitter.com/cdathuraliya> | Blog <https://cdathuraliya.wordpress.com/>
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