• 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

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}}
}