Re: [neuralnet] v0.3

Damn, I have the [omniFilter_abs~] there too? I missed that. You can get 
it here https://github.com/alexdrymonitis/filter_abstractions

The [command] object is a replacement of [shell]. If I'm not mistaken, 
it doesn't work on Windows. You don't necessarily need it though, I use 
it to load training data, but I do provide trained models, so you can 
test them without needing to train them from scratch.

That's strange with [neuralnet~]. Do you have the respective binary?

On 9/17/24 10:22, João Pais wrote:
>
>> This abstraction is in the examples/abstractions directory. I just 
>> realised that I have my local osc_abs prepended to the abstraction 
>> name. Just remove that and it should load.
>>
> Ah yes - but then the omniFilter_abs~ is also not present. Also the 
> [command] object isn't loaded, from which library does it come?
>
> Strangely, on 06 and 07 examples, [neuralnet~ 
> models/audio_autoencoder~ encoder] doesn't create, but [neuralnet 
> models/audio_autoencoder~ encoder] does. (I'm on windows)
>
>> Well, using a neural network boils down to the training dataset that 
>> you'll assemble. Get as many input/output combinations as you can. 
>> Then you'll have to choose the right structure and activation and 
>> loss functions, plus optimizer (although, usually the latter is an Adam).
>>
>> Your question is a bit vague, and explaining how to set up a neural 
>> network in an email is not an easy task. Especially for me, since I'm 
>> not an expert (even though I coded this library).
>>
> that's true. in this context, it would envolve getting a 1-(or 
> 2-)dimensional data, and detecting a pattern over time (probably 
> between 0.1 and 1.5 seconds).
>
>
>> Cheers
>>
>> On 9/15/24 23:37, João Pais wrote:
>>>
>>> Hi, is the patch osc_abs/fm_3 missing from the package?
>>>
>>> I'm looking for a way to make a model for leapmotion to recognize 
>>> gestures (coming from combinations of xyz or velocity vectores for 
>>> each finger, for example). Would you advise using this library for this?
>>>
>>> Best,
>>>
>>> JOao
>>>
>>>
>>>> [neuralnet] update! Version 0.3 has just been released!
>>>>
>>>>   * New activation functions added
>>>>   * Access to the internal structure of a trained network (e.g. the
>>>>     latent space)
>>>>   * Storing weights and biases during training for visualization
>>>>   * Save models during training
>>>>   * Signal-rate version of the object!
>>>>   * Audio autoencoder example added!
>>>>
>>>> Binaries for Linux, Raspberry Pi 3,4,5, macOS, and Windows (thanks 
>>>> Ben Wesch for macOS and Windows) are available through deken.
>>>> Souces are available on 
>>>> GitHubhttps://github.com/alexdrymonitis/neuralnet
>>>> Thanks to Ben Wesch, Dan Wilcox, IOhannes m zmoelnig, Christof 
>>>> Ressi, and others!
>>>>
>>>> Enjoy!
>>>>
>
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