zaneCC's Stars
pytorch/pytorch
Tensors and Dynamic neural networks in Python with strong GPU acceleration
labmlai/annotated_deep_learning_paper_implementations
🧑🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
mli/paper-reading
深度学习经典、新论文逐段精读
junyanz/pytorch-CycleGAN-and-pix2pix
Image-to-Image Translation in PyTorch
timqian/chinese-independent-blogs
中文独立博客列表
microsoft/LightGBM
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
eriklindernoren/PyTorch-GAN
PyTorch implementations of Generative Adversarial Networks.
Embedding/Chinese-Word-Vectors
100+ Chinese Word Vectors 上百种预训练中文词向量
marcotcr/lime
Lime: Explaining the predictions of any machine learning classifier
wandb/wandb
The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.
autogluon/autogluon
Fast and Accurate ML in 3 Lines of Code
PaddlePaddle/models
Officially maintained, supported by PaddlePaddle, including CV, NLP, Speech, Rec, TS, big models and so on.
zhangqianhui/AdversarialNetsPapers
Awesome paper list with code about generative adversarial nets
rasbt/mlxtend
A library of extension and helper modules for Python's data analysis and machine learning libraries.
martinarjovsky/WassersteinGAN
dreamquark-ai/tabnet
PyTorch implementation of TabNet paper : https://arxiv.org/pdf/1908.07442.pdf
SeldonIO/alibi
Algorithms for explaining machine learning models
CoinCheung/pytorch-loss
label-smooth, amsoftmax, partial-fc, focal-loss, triplet-loss, lovasz-softmax. Maybe useful
manujosephv/pytorch_tabular
A standard framework for modelling Deep Learning Models for tabular data
sdv-dev/CTGAN
Conditional GAN for generating synthetic tabular data.
yandex-research/rtdl
Research on Tabular Deep Learning: Papers & Packages
lucidrains/tab-transformer-pytorch
Implementation of TabTransformer, attention network for tabular data, in Pytorch
YyzHarry/imbalanced-regression
[ICML 2021, Long Talk] Delving into Deep Imbalanced Regression
vandit15/Class-balanced-loss-pytorch
Pytorch implementation of the paper "Class-Balanced Loss Based on Effective Number of Samples"
OpenRL-Lab/Wandb_Tutorial
How to use wandb?
Diyago/Tabular-data-generation
We well know GANs for success in the realistic image generation. However, they can be applied in tabular data generation. We will review and examine some recent papers about tabular GANs in action.
Aixile/chainer-cyclegan
Chainer CycleGAN
albahnsen/CostSensitiveClassification
CostSensitiveClassification Library in Python
xungeer29/Classic-DeepLearning-Papers
经典深度学习论文集
pengwei-iie/Llama2-Chinese
reproduce of FlagAlpha/Llama2-Chinese