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ml-nlp

此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现，也是作为一个算法工程师必会的理论基础知识。

mle-interview

该仓库记录搜索推荐算法工程师的必备面试知识点+paper

molclr

Implementation of "Molecular Contrastive Learning of Representations via Graph Neural Networks" in PyTorch Geometric

molecule-design-tools

molvae

Molecule Generation and Translation Framework. This is a joint PyTorch implementation of three papers in VAE-based molecule generation and translation including JTVAE, V-JTNN-GAN, HierVAE and HierVGNN

mystars

很棒的列表，主要是机器学习、深度学习、NLP、GNN、推荐系统、生物医药、机器视觉等内容。持续更新！欢迎star！欢迎star！😀😀😀

nlp-journey

Documents, papers and codes related to Natural Language Processing, including Topic Model, Word Embedding, Named Entity Recognition, Text Classificatin, Text Generation, Text Similarity, Machine Translation)，etc. All codes are implemented intensorflow 2.0.

nlp-paper

自然语言处理领域下的对话语音领域，整理相关论文（附阅读笔记），复现模型以及数据处理等（代码含TensorFlow和PyTorch两版本）

nlp-tutorial

Natural Language Processing Tutorial for Deep Learning Researchers

pgl

Paddle Graph Learning (PGL) is an efficient and flexible graph learning framework based on PaddlePaddle

pretrain_model

python-100-days

Python - 100天从新手到大师

pytorch-distributed-training

Simple tutorials on Pytorch DDP training

pytorch_utils

A useful PyTorch library with several useful tools and training tricks.

pytorchtricks

Some tricks of pytorch... :star:

qsar_intro

ray-pytorch-starter-code

Example code for getting started with Ray + PyTorch

reclearn

Recommender Learning with Tensorflow2.x

recommend-tf2.0senet

推荐系统之深度学习模型，框架采用tensorflow2

recsys_structured_streaming

kafka + structured streaming + phoenix + elasticsearch 基于行为日志实现热门推荐，用户偏好推荐，召回融合策略实现。

semi-supervised-learning

A Unified Semi-Supervised Learning Codebase (NeurIPS'22)

timeseries

traffic-benchmark

tuning_playbook

A playbook for systematically maximizing the performance of deep learning models.

uni-core

an efficient distributed PyTorch framework

uni-mol

Official Repository for the Uni-Mol Series Methods

viton-gan

Original implementation of the paper "VITON-GAN: Virtual Try-on Image Generator Trained with Adversarial Loss" by Shion Honda.

yk-liu.github.io

Pointing to the Moon, my personal website.