Hello, I have finally added a configuration to the NeuralNetwork project. Now you can use this Metacello script to load it into your Pharo image:
Metacello new repository: 'http://smalltalkhub.com/mc/Oleks/NeuralNetwork/main'; configuration: 'MLNeuralNetwork'; version: #development; load. Sorry for the delay Oleks On Tue, Apr 25, 2017 at 4:13 PM, francescoagati [via Smalltalk] < ml+s1294792n4944028...@n4.nabble.com> wrote: > thanks ;-) > > 2017-04-25 15:09 GMT+02:00 Oleks <[hidden email] > <http:///user/SendEmail.jtp?type=node&node=4944028&i=0>>: > >> Hello, >> >> There isn't one yet. But I will try to create it today. I will let you >> know >> >> Cheers, >> Oleks >> >> On Apr 25, 2017 16:10, "francescoagati [via Smalltalk]" <[hidden email] >> <http:///user/SendEmail.jtp?type=node&node=4944027&i=0>> wrote: >> >>> Hi Oleks, >>> there is a mode for install neural network from metacello? >>> >>> 2017-04-25 13:00 GMT+02:00 Alexandre Bergel <[hidden email] >>> <http:///user/SendEmail.jtp?type=node&node=4944025&i=0>>: >>> >>>> Continue to push that topic Oleks. You are on the right track! >>>> >>>> Alexandre >>>> >>>> > On Apr 24, 2017, at 1:43 AM, Oleks <[hidden email] >>>> <http:///user/SendEmail.jtp?type=node&node=4944025&i=1>> wrote: >>>> > >>>> > Hello, >>>> > >>>> > Thanks a lot for your advice! It was very helpful and educating (for >>>> > example, I thought that we store biases in the weight matrix and >>>> prepend 1 >>>> > to input to make it faster, but now I see why it's actually slower >>>> that >>>> > way). >>>> > >>>> > I've implemented a multi-layer neural network as a linked list of >>>> layers >>>> > that propagate the input and error from one to another, similar to >>>> the Chain >>>> > of Responsibility pattern. Also, now I represent biases as separate >>>> vectors. >>>> > The LearningAlgorithm is a separate class with Backpropagation as its >>>> > subclass (though at this point the network can only learn through >>>> > backpropagation, but I'm planning to change that). I'm trying to >>>> figure out >>>> > how the activation and cost functions should be connected. For >>>> example, >>>> > cross-entropy works best with logistic sigmoid activation etc. I >>>> would like >>>> > to give the user a freedom to use whatever he wants (plug in whatever >>>> you >>>> > like and see what happens), but it can be very inefficient (because >>>> some >>>> > time-consuming parts of activation and cost derivatives cancel out >>>> each >>>> > other). >>>> > >>>> > Also, there is an interface for setting the learning rate for the >>>> whole >>>> > network, which can be used to choose the learning rate prior to >>>> learning, as >>>> > well as to change the learning rate after each iteration. I am >>>> planning to >>>> > implement some optimization algorithms that would automize the >>>> process of >>>> > choosing a learning rate (adagrad for example), but this would >>>> require a bit >>>> > different design (maybe I will implement the Optimizer, as you >>>> suggested). >>>> > >>>> > I'm attaching two images with UML diagrams, describing my current >>>> > implementation. Could you please tell me what you think about this >>>> design? >>>> > The first image is a class diagram that shows the whole architecture, >>>> and >>>> > the second one is a sequence diagram of backpropagation. >>>> > >>>> > mlnn.png <http://forum.world.st/file/n4943698/mlnn.png> >>>> > backprop.png <http://forum.world.st/file/n4943698/backprop.png> >>>> > >>>> > Sincerely yours, >>>> > Oleksandr >>>> > >>>> > >>>> > >>>> > -- >>>> > View this message in context: http://forum.world.st/Neural-N >>>> etworks-in-Pharo-tp4941271p4943698.html >>>> > Sent from the Pharo Smalltalk Users mailing list archive at >>>> Nabble.com. >>>> > >>>> >>>> -- >>>> _,.;:~^~:;._,.;:~^~:;._,.;:~^~:;._,.;:~^~:;._,.;: >>>> Alexandre Bergel http://www.bergel.eu >>>> ^~:;._,.;:~^~:;._,.;:~^~:;._,.;:~^~:;._,.;:~^~:;. >>>> >>>> >>>> >>>> >>>> >>> >>> >>> ------------------------------ >>> If you reply to this email, your message will be added to the discussion >>> below: >>> http://forum.world.st/Neural-Networks-in-Pharo-tp4941271p4944025.html >>> To unsubscribe from Neural Networks in Pharo, click here. >>> NAML >>> <http://forum.world.st/template/NamlServlet.jtp?macro=macro_viewer&id=instant_html%21nabble%3Aemail.naml&base=nabble.naml.namespaces.BasicNamespace-nabble.view.web.template.NabbleNamespace-nabble.view.web.template.NodeNamespace&breadcrumbs=notify_subscribers%21nabble%3Aemail.naml-instant_emails%21nabble%3Aemail.naml-send_instant_email%21nabble%3Aemail.naml> >>> >> >> ------------------------------ >> View this message in context: Re: Neural Networks in Pharo >> <http://forum.world.st/Neural-Networks-in-Pharo-tp4941271p4944027.html> >> >> Sent from the Pharo Smalltalk Users mailing list archive >> <http://forum.world.st/Pharo-Smalltalk-Users-f1310670.html> at >> Nabble.com. >> > > > > ------------------------------ > If you reply to this email, your message will be added to the discussion > below: > http://forum.world.st/Neural-Networks-in-Pharo-tp4941271p4944028.html > To unsubscribe from Neural Networks in Pharo, click here > <http://forum.world.st/template/NamlServlet.jtp?macro=unsubscribe_by_code&node=4941271&code=b2xrLnpheXRzZXZAZ21haWwuY29tfDQ5NDEyNzF8MTQxNTM2ODEzNw==> > . > NAML > <http://forum.world.st/template/NamlServlet.jtp?macro=macro_viewer&id=instant_html%21nabble%3Aemail.naml&base=nabble.naml.namespaces.BasicNamespace-nabble.view.web.template.NabbleNamespace-nabble.view.web.template.NodeNamespace&breadcrumbs=notify_subscribers%21nabble%3Aemail.naml-instant_emails%21nabble%3Aemail.naml-send_instant_email%21nabble%3Aemail.naml> > -- View this message in context: http://forum.world.st/Neural-Networks-in-Pharo-tp4941271p4944473.html Sent from the Pharo Smalltalk Users mailing list archive at Nabble.com.
