Pytorch Tutorial Python Packages

zetascale

Build high-performance AI models with modular building blocks

mitdeeplearning

Lab Materials for MIT 6.S191: Introduction to Deep Learning

pytorch-accelerated

A lightweight library designed to accelerate the process of training PyTorch models by providing a minimal, but extensible training loop which is flexible enough to handle the majority of use cases, and capable of utilizing different hardware options with no code changes required. Docs: https://pytorch-accelerated.readthedocs.io/en/latest/

torchensemble

A unified ensemble framework for PyTorch to improve the performance and robustness of your deep learning model.

blitz-bayesian-pytorch

A simple and extensible library to create Bayesian Neural Network layers on PyTorch.

early-stopping-pytorch

Early stopping for PyTorch

cub-tools

A set of notebooks as a guide to the process of fine-grained image classification of birds species, using PyTorch based deep neural networks.

vit-trainer

Explore fine-tuning the Vision Transformer (ViT) model for object recognition in robotics using PyTorch. This tutorial covers setup, training, and evaluation processes, achieving impressive accuracy with practical resource constraints. Ideal for learners in AI and robotics.

paramfittorchdemo

How to use pytorch to fit parameters of differential equations

torchlib

A best practice for deep learning project template architecture.

splearn

splearn: package for signal processing and machine learning with Python. Contains tutorials on understanding and applying signal processing.