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.
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).
Cheers
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 GitHub https://github.com/alexdrymonitis/neuralnet
Thanks to Ben Wesch, Dan Wilcox, IOhannes m zmoelnig, Christof Ressi, and others!Enjoy!
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