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Here I'm gonna kickstart first iteration of notebook for neural nets with numpy and scipy following:
- *instruction*, 30m: crash course in neural networks
+ along with live demo in Numpy
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**Lecture Courses**
http://www.robots.ox.ac.uk/~az/lectures/
https://www.gaussianwaves.com/2013/11/simulation-and-analysis-of-white-noise-in-matlab/
https://github.com/oxford-cs-deepnlp-2017
http…
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Welcome to 'DSWP' Team, good to see you here.
This issue will helps readers in acquiring all the knowledge to learn about getting involved with Activation Functions in Neural Networks. Tutorial to …
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**Is your feature request related to a problem? Please describe.**
I'm a GSSoC'23 Contributor.
As Face-X repo has numerous projects on facial recognition and other things. So, it would be a better…
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**Title` of the quantum algorithm**
Demonstration for Quantum Convolutional Neural Network with Chest X-ray Pneumonia Dataset
**Description of the quantum algorithm**
Quantum Convolutional Neur…
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The Post-Doc positions is in Deep Learning for climate change impacts/mitigation, with a particular emphasis on convolutional neural networks (CNNs) application.
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- [x] Gradient enhanced kriging (https://smt.readthedocs.io/en/latest/_src_docs/surrogate_models/gekpls.html)
- [ ] Gradient enhanced neural networks (https://smt.readthedocs.io/en/latest/_src_docs/s…
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Research a few possible models we can use to generate text. Possibilities:
* Markov chains: should be relatively easy to implement on our own but likely wouldn't give great results.
* Recurrent ne…
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apparently sigmoid activation functions are not how most modern neural networks are done anymore and [ReLUs](https://en.wikipedia.org/wiki/Rectifier_(neural_networks)) are easier to train
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Having a way to save/restore the state of the compiled DSP could be interesting for neural networks kind of use-cases, or easing saving/restoring presets.
sletz updated
2 years ago