Pytorch

entities · 16 notes linked

Related: Deep Learning · Transformers · Gradient Descent · Automatic Differentiation · Attention Mechanism · Positional Encoding · Generative Adversarial Networks · Neural Networks

Notes

• A detailed example of how to generate your data in parallel with PyTorch Star — Using PyTorch Dataset and DataLoader with multicore parallel data generation
• Building a Simple Python-Based GAN in 5 minutes — Minimal PyTorch GAN with generator-discriminator adversarial training loop
• Getting Started With Pytorch In Google Collab With Free GPU — Beginner tutorial on PyTorch tensors and autograd using free Colab GPU
• GitHub - pfnet/pfrl: PFRL: a PyTorch-based deep reinforcement learning library — PyTorch open-source library implementing state-of-the-art deep RL algorithms
• GitHub - sainathadapa/attention-primer-pytorch — PyTorch toy tasks demonstrating attention mechanisms from Vaswani et al.
• GitHub - sktime/pytorch-forecasting: Time series forecasting with PyTorch — High-level PyTorch library for deep learning time series forecasting
• Gradient descent for linear regression using PyTorch — PyTorch tutorial implementing minibatch SGD for least-squares linear regression
• Implementation differences in LSTM layers- Tensorflow vs Pytorch | Towards Data Science — API and parameter differences in LSTM layer implementations across TF and PyTorch
• Learn PyTorch for Deep Learning – Free 26-Hour Course — Free 26-hour hands-on PyTorch deep learning course for beginners
• PyTorch Explained: From Automatic Differentiation to Training Custom Neural Networks | Towards Data Science — PyTorch core abstractions from tensors and autograd to transformer encoder
• PyTorch-GAN vanilla GAN implementation — Reference PyTorch implementation of vanilla GAN on MNIST
• Running PyTorch on the M1 GPU — Benchmark of PyTorch M1 GPU support via MPS backend for deep learning training
• The Annotated Transformer — Line-by-line annotated implementation of Attention Is All You Need
• The Matrix Calculus You Need For Deep Learning — Matrix calculus tutorial covering gradients and Jacobians for neural network training
• Welcome to the UvA Deep Learning Tutorials! — University of Amsterdam Jupyter notebook deep learning course covering PyTorch and JAX
• What is nn.Embedding really? — PyTorch embedding layer as efficient lookup-based linear layer equivalent