mlnomadpy

4 ms·

1.
by mlnomadpy 1y ago
yes, since you can learn to represent the same problem with less amount of params, however most of the architectures are optimized for the linear product, so we gotta figure out a new architecture for it
2.
by mlnomadpy 1y ago
they are one of the reasons neural networks are blackbox, we lose information about the data manifold the deeper we go in the network, making it impossible to trace back the output this preprint is not coming from a standpoint of optimizing
3.
by mlnomadpy 1y ago
that's a great point you made, but the goal of this research paper is not to improve the performance, but to show that you can train deep neural networks without the need of activation functions, normalization layers, deep neural netwo
4.
by mlnomadpy 1y ago
basicly the real "non-linearity" in deep learning have always been the orthogonality, squashing functions make it easy for the neurons to tap into the orthogonality, while most of the activation functions "lie" about the
5.
by mlnomadpy 1y ago
indeed, there is an extensive work done in kernel learning that is facinating and one of the applications that still do these transformations are satellite imagery/multispectral imagery, you can get more information just from calculat
6.
Do you hate Jupyter notebooks? introducing bashnota (Open Source)(offline.bashnota.com)
2 points by mlnomadpy 1y ago|1 comments
7.
Neural networks that learn non-linearity without activation functions [pdf](tahabouhsine.com)
23 points by mlnomadpy 1y ago|12 comments
8.
by mlnomadpy 1y ago
hello everyone, am taha, I was able to create a new kernel that allows you to learn non-linearity without using activation functions, making the models whitebox, and without any information loss. MiniGPT with huggingface datasets streaming:
9.
Open source Jupyter notebooks alternative with a Notion like UX(offline.bashnota.com)
2 points by mlnomadpy 1y ago|1 comments
10.
by mlnomadpy 1y ago
We built a Notion-style alternative to Jupyter notebooks with local AI built-in. Connect to your own Jupyter server and run code seamlessly. It's a PWA that runs entirely on your local machine. No vendor lock-in, no data sent to the cl