GenjiLuo

GenjiLuo's Stars

• Chanzhaoyu/chatgpt-web

  用 Express 和 Vue3 搭建的 ChatGPT 演示网页

  Language:Vue31.5k11.2k

• Arvintian/chatgpt-web

  ChatGPT Web App implemented in golang based on OpenAI API.

  Language:Go9123

• linhaojun857/aurora

  基于SpringBoot+Vue开发的个人博客系统

  Language:Java4k664

• jiqizhixin/SyncedLeg2018

  SyncedLeg - A Customizable Tool For Mining Influential Keywords From Large Corpus

  Language:Python195

• jiqizhixin/AI-Terminology-page

  The English-Chinese paired terminologies in Artificial Intelligence Domain

  11726

• jiqizhixin/Artificial-Intelligence-Terminology-Database

  A comprehensive mapping database of English to Chinese technical vocabulary in the artificial intelligence domain

  1.9k330

• liuhuanyong/DomainWordsDict

  DomainWordsDict, Chinese words dict that contains more than 68 domains, which can be used as text classification、knowledge enhance task。涵盖68个领域、共计916万词的专业词典知识库，可用于文本分类、知识增强、领域词汇库扩充等自然语言处理应用。

  655111

• iawia002/lux

  👾 Fast and simple video download library and CLI tool written in Go

  Language:Go27.6k3k

• cubewise-code/sweetssl

  SweetSSL is a lightweight easy to use reverse proxy written in Go that provides FREE Let's Encrypt SSL certificates

  Language:Go121

• SpiderLabs/HostHunter

  HostHunter a recon tool for discovering hostnames using OSINT techniques.

  Language:Python1.1k181

• PengJenas/MineWechat

  python小工具，微信群发、自动回复、手机微信简单远控电脑

  Language:Python15045

• GenjiLuo/Attention-as-Dynamic-Tf-Idf-for-Deep-Learning

  Implementing attention to recover task specific weighting of words

  1

• Tixierae/deep_learning_NLP

  Keras, PyTorch, and NumPy Implementations of Deep Learning Architectures for NLP

  Language:Jupyter Notebook435104

• cedrickchee/awesome-transformer-nlp

  A curated list of NLP resources focused on Transformer networks, attention mechanism, GPT, BERT, ChatGPT, LLMs, and transfer learning.

  1.1k129

• mesolitica/NLP-Models-Tensorflow

  Gathers machine learning and Tensorflow deep learning models for NLP problems, 1.13 < Tensorflow < 2.0

  Language:Jupyter Notebook1.8k730

• graykode/nlp-tutorial

  Natural Language Processing Tutorial for Deep Learning Researchers

  Language:Jupyter Notebook14.2k3.9k

• micmro/performance-bookmarklet

  Performance-Bookmarklet helps to analyze the current page through the Resource Timing API, Navigation Timing API and User-Timing - requests by type, domain, load times, marks and more. Sort of a light live WebPageTest.

  Language:JavaScript1.1k87

• kisslove/web-monitoring

  前端监控，性能监控平台。前端监控平台专注于Web端体验数据监控。对网页健康状况的三个方面进行监测：页面打开速度（速度测量）、页面稳定性（JS错误）和外部服务调用成功率（API）

  Language:JavaScript1k192

• TeaWeb/build

  TeaWeb-可视化的Web代理服务。DEMO: http://teaos.cn:7777

  Language:Go769184

• onblog/BlogHelper

  帮助国内用户写作的托盘助手，一键发布本地文章到主流博客平台（知乎、简书、博客园、CSDN、SegmentFault、掘金、开源**），剪贴板图片一键上传至图床（新浪、Github、图壳、腾讯云、阿里云、又拍云、七牛云）（欢迎Star，🚫禁止Fork）

  Language:JavaScript1.9k283

• YellowLabTools/YellowLabTools

  WebPerf and front-end quality testing tool

  Language:JavaScript2.4k121

• openatx/facebook-wda

  Facebook WebDriverAgent Python Client Library (not official)

  Language:Python1.7k266

• openatx/uiautomator2

  Android Uiautomator2 Python Wrapper

  Language:Python6.6k1.4k

• gorilla/websocket

  Package gorilla/websocket is a fast, well-tested and widely used WebSocket implementation for Go.

  Language:Go22.4k3.5k

• magic-FE/translate-man

  An excellent google translation plug-in, you will love it

  Language:JavaScript27740

• songhengyang/face_landmark_factory

  These are a set of tools using OpenCV, Tensorflow and Keras, with which you can generate your own model of facial landmark detection and demonstrate the effect of newly-generated model easily.

  Language:Python13840

• dnSpy/dnSpy

  .NET debugger and assembly editor

  Language:C#26.6k5.1k

• aika-algorithm/aika

  AIKA is a new type of artificial neural network designed to more closely mimic the behavior of a biological brain and to bridge the gap to classical AI. A key design decision in the Aika network is to conceptually separate the activations from their neurons, meaning that there are two separate graphs. One graph consisting of neurons and synapses representing the knowledge the network has already acquired and another graph consisting of activations and links describing the information the network was able to infer about a concrete input data set. There is a one-to-many relation between the neurons and the activations. For example, there might be a neuron representing a word or a specific meaning of a word, but there might be several activations of this neuron, each representing an occurrence of this word within the input data set. A consequence of this decision is that we have to give up on the idea of a fixed layered topology for the network, since the sequence in which the activations are fired depends on the input data set. Within the activation network, each activation is grounded within the input data set, even if there are several activations in between. This means links between activations serve two purposes. On the one hand, they are used to sum up the synapse weights and, on the other hand they propagate the identity to higher level activations.

  Language:Java7519

• mayurkaul/medialibrary

  This library is inspired with the Album structure of the Android Gallery and has abstracted library to get the Albums Data structure for Photos, Videos or All based on the Clustering of Photos based on Album, time, location, Tag, Size, etc.

  Language:Java228

• qieangel2013/zys

  high performance service framework based on Yaf or Swoole

  Language:PHP791255