/10-days-of-grad

Neural Networks and Deep Learning

Primary LanguageJupyter Notebook

10 Days Of Grad: Deep Learning From The First Principles

Neural networks in Haskell

  • Day 1: Neural network basics
  • Day 2: Multilayer neural networks
  • Day 3: Automatic differentiation
  • Day 4: Batch normalization and MNIST images
  • Day 5: Convolutional neural networks
  • Day 6: Binarized neural networks
  • Day 7: Deep Learning with Hasktorch
  • Day 8: Model Uncertainty Estimation
  • Day 9: Variational Autoencoders
  • Day 10: Deep Reinforcement Learning

Citation

BibTeX:

@misc{tendays,
  author = {Penkovsky, Bogdan},
  title = {10 Days of Grad: Neural Networks and Deep Learning},
  year = {2023},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/masterdezign/10-days-of-grad}}
}