The Yann LeCun et al. (1989) paper on Backpropagation Applied to Handwritten Zip Code Recognition is a significant piece of deep learning history. Despite its age, the paper’s content remains remarkably modern, outlining dataset creation, neural network architecture, optimization techniques, and classification error rates. The author set out to reproduce the paper’s results using PyTorch and made slight improvements by adjusting loss functions, optimization algorithms, and introducing data augmentation and dropout techniques. They also noted that scaling up the dataset could further enhance performance. Ultimately, the exercise demonstrated the advancements in deep learning over the past 33 years but also highlighted the limitations of network size and computational resources. The author predicts that future trends will involve fine-tuning pre-trained models rather than training from scratch.
http://karpathy.github.io/2022/03/14/lecun1989/