Hydra is a framework for elegantly configuring complex applications

Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

Apache Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadata. Runs and scales everywhere python does.

A curated list of practical guide resources of LLMs (LLMs Tree, Examples, Papers)

End-to-End Object Detection with Transformers

The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (V…

VISSL is FAIR's library of extensible, modular and scalable components for SOTA Self-Supervised Learning with images.

Latex code for making neural networks diagrams

PyTorch implementation of Contrastive Learning methods

OpenMMLab Self-Supervised Learning Toolbox and Benchmark

Statistische Analyse und Visualisierung der täglichen Diagnoseschlüssel der deutschen COVID-19 Tracing-App (Corona-Warn-App).

Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.

Flax is a neural network library for JAX that is designed for flexibility.

The pytorch re-implement of the official efficientdet with SOTA performance in real time and pretrained weights.

A curated list of articles that cover the software engineering best practices for building machine learning applications.

Paper by Miyato et al. https://openreview.net/forum?id=B1QRgziT-

tensorboard for pytorch (and chainer, mxnet, numpy, ...)

Summaries of machine learning papers

DeepPose implementation on TensorFlow. Original Paper http://arxiv.org/abs/1312.4659

An Open Source Machine Learning Framework for Everyone