sirgarfieldc's Stars
Billy1900/Ethereum-tutorial
Awesome analysis of Ethereum source code, Chinese version
0xemperor/Awesome-MEV
A list of MEV resources with a focus on past research papers/talks.
scaffold-eth/scaffold-eth
🏗 forkable Ethereum dev stack focused on fast product iterations
botcrypto-io/awesome-crypto-trading-bots
Awesome crypto trading bots
Defi-Cartel/salmonella
Wrecking sandwich traders for fun and profit
mahmoodlab/CLAM
Data-efficient and weakly supervised computational pathology on whole slide images - Nature Biomedical Engineering
HobbitLong/SupContrast
PyTorch implementation of "Supervised Contrastive Learning" (and SimCLR incidentally)
google-research/google-research
Google Research
junyanz/pytorch-CycleGAN-and-pix2pix
Image-to-Image Translation in PyTorch
phillipi/pix2pix
Image-to-image translation with conditional adversarial nets
ultralytics/yolov5
YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
Lightning-AI/pytorch-lightning
Pretrain, finetune and deploy AI models on multiple GPUs, TPUs with zero code changes.
pytorch/ignite
High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently.
ajabri/videowalk
Repository for "Space-Time Correspondence as a Contrastive Random Walk" (NeurIPS 2020)
silencial/DeepRL
Berkeley CS285 2019 homework solution
zcaceres/fastai-audio
collaborative audio module for fast.ai
koukyo1994/kaggle-birdcall-6th-place
Training code of Cornell Birdcall Identification Challenge 6th place solution
qiuqiangkong/torchlibrosa
qiuqiangkong/sed_time_freq_segmentation
Morizeyao/GPT2-Chinese
Chinese version of GPT2 training code, using BERT tokenizer.
facebookresearch/detectron2
Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.
instillai/TensorFlow-Course
:satellite: Simple and ready-to-use tutorials for TensorFlow
bharathgs/Awesome-pytorch-list
A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.
floodsung/Deep-Learning-Papers-Reading-Roadmap
Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!
GokuMohandas/Made-With-ML
Learn how to design, develop, deploy and iterate on production-grade ML applications.
aleju/imgaug
Image augmentation for machine learning experiments.