Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Added Deep Learning with PyTorch, Second Edition #136

Open
wants to merge 1 commit into
base: master
Choose a base branch
from
Open

Added Deep Learning with PyTorch, Second Edition #136

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
1 change: 1 addition & 0 deletions README.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -357,6 +357,7 @@ Demonstration of training a small ResNet on CIFAR10 to 94% test accuracy in 79 s
70. [Serverless Machine Learning in Action with PyTorch and AWS](https://www.manning.com/books/serverless-machine-learning-in-action): Serverless Machine Learning in Action is a guide to bringing your experimental PyTorch machine learning code to production using serverless capabilities from major cloud providers like AWS, Azure, or GCP.
71. [LabML NN](https://github.com/lab-ml/nn): A collection of PyTorch implementations of neural networks architectures and algorithms with side-by-side notes.
72. [Run your PyTorch Example Fedarated with Flower](https://github.com/adap/flower/tree/main/examples/pytorch_from_centralized_to_federated): This example demonstrates how an already existing centralized PyTorch machine learning project can be federated with Flower. A Cifar-10 dataset is used together with a convolutional neural network (CNN).
73. [Deep Learning with PyTorch, Second Edition](https://www.manning.com/books/deep-learning-with-pytorch-second-edition): A hands-on guide to modern machine learning with PyTorch.

## Paper implementations

Expand Down