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a-pytorch-tutorial-to-object-detection

SSD: Single Shot MultiBox Detector | a PyTorch Tutorial to Object Detection

aiocrawler

baai-zhihu-2019

智源 - 看山杯 专家发现算法大赛 2019 7th (https://www.biendata.com/competition/zhihu2019/)

chrome-extension-webpack-boilerplate

A basic foundation boilerplate for rich Chrome Extensions using Webpack to help you write modular and modern Javascript code, load CSS easily and automatic reload the browser on code changes.

coder2gwy

互联网首份程序员考公指南，由3位已经进入体制内的前大厂程序员联合献上。

dapr

Dapr is a portable, event-driven, runtime for building distributed applications across cloud and edge.

featurelearningrotnet

feedray

imageflow

Simple image flow with Pixiv images.

leakgan

The codes of paper "Long Text Generation via Adversarial Training with Leaked Information" on AAAI 2018. Text generation using GAN and Hierarchical Reinforcement Learning.

modelsgenesis

Official Keras & PyTorch Implementation and Pre-trained Models for Models Genesis - MICCAI 2019

opennmt-py

Open Source Neural Machine Translation in PyTorch

pytorch-pretrained-bert

📖The Big-&-Extending-Repository-of-Transformers: Pretrained PyTorch models for Google's BERT, OpenAI GPT & GPT-2, Google/CMU Transformer-XL.

pytorch-yolov3

Minimal PyTorch implementation of YOLOv3

qasystemonmedicalkg

A tutorial and implement of disease centered Medical knowledge graph and qa system based on it。知识图谱构建，自动问答，基于kg的自动问答。以疾病为中心的一定规模医药领域知识图谱，并以该知识图谱完成自动问答与分析服务。

rayonfire.github.io

revisiting-self-supervised

scikit-learn

scikit-learn: machine learning in Python

seqgan-pytorch

A implementation of SeqGAN in PyTorch, following the implementation in tensorflow.

servlet-authntication

simclr

SimCLRv2 - Big Self-Supervised Models are Strong Semi-Supervised Learners

spider-backend

Dashboard for aiocrawler

spring-demo

springlearner

tf-estimator-tutorials

This repository includes tutorials on how to use the TensorFlow estimator APIs to perform various ML tasks, in a systematic and standardised way

word2vecpy

Python implementation of CBOW and skip-gram word vector models, and hierarchical softmax and negative sampling learning algorithms