random-neural-net-models 0.2.0

My implementation of a random selection of artificial neural net based models.

random neural nets

Implementations of a random selection of artificial neural net based models and methods.

Python version

Development is done using pyenv, pinning the python version to the one in the file .python-version.

Installation (on Linux)

Package + notebooks:

git clone https://github.com/eschmidt42/random-neural-net-models.git
cd random-neural-net-models
make install

Package only:

pip install random-neural-net-models

Usage

See jupyter notebooks in nbs/ for:

• perceptron: perceptron.ipynb
• backpropagation: backpropagation_rumelhart1986.ipynb
• convolution: convolution_lecun1990.ipynb
• cnn autoencoder:
  • mnist: cnn_autoencoder_fastai2022.ipynb
  • fashion mnist: cnn_autoencoder_fastai2022_fashion.ipynb
• variational autoencoder:
  • dense: dense_variational_autoencoder_fastai2022.ipynb
  • cnn+dense: cnn_variational_autoencoder_fastai2022.ipynb
• optimizers: stochastic_optimization_methods.ipynb
• resnet: resnet_fastai2022.ipynb
• unet: unet_fastai2022.ipynb
• diffusion (unet + noise): diffusion_fastai2022.ipynb
• mingpt:
  • mingpt_sort.ipynb
  • mingpt_char.ipynb
  • mingpt_adder.ipynb