Stars
Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.
JavaScript API for Chrome and Firefox
Repository for benchmarking graph neural networks (JMLR 2023)
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (V…
Paddle Graph Learning (PGL) is an efficient and flexible graph learning framework based on PaddlePaddle
🤖 A Python library for learning and evaluating knowledge graph embeddings
Transformers for Information Retrieval, Text Classification, NER, QA, Language Modelling, Language Generation, T5, Multi-Modal, and Conversational AI
🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.
We provide a PyTorch implementation of the paper Voice Separation with an Unknown Number of Multiple Speakers In which, we present a new method for separating a mixed audio sequence, in which multi…
Learning Embeddings that Capture Spatial Semantics for Indoor Navigation, NeurIPS ORLR 2020
Graph Neural Networks with Keras and Tensorflow 2.
Gathers machine learning and Tensorflow deep learning models for NLP problems, 1.13 < Tensorflow < 2.0
metapath2vec: Scalable Representation Learning for Heterogeneous Networks(KDD 2017) in Tensorflow
Public release of the TransCoder research project https://arxiv.org/pdf/2006.03511.pdf
The easiest way to serve AI apps and models - Build Model Inference APIs, Job queues, LLM apps, Multi-model pipelines, and more!
Hummingbird compiles trained ML models into tensor computation for faster inference.
A library of reinforcement learning components and agents
pipreqs - Generate pip requirements.txt file based on imports of any project. Looking for maintainers to move this project forward.
The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relating to PyTorch.
Lightweight implementations of generative label models for weakly supervised machine learning
Training neural models with structured signals.
Learn about Machine Learning and Artificial Intelligence
Best practice and tips & tricks to write scientific papers in LaTeX, with figures generated in Python or Matlab.
VIP cheatsheets for Stanford's CS 229 Machine Learning
NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.
A collection of important graph embedding, classification and representation learning papers with implementations.
A Python-embedded modeling language for convex optimization problems.
Identify nerve structures in ultrasound images of the neck on Kaggle